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Qualitative Research in Nursing“Not everything that counts can be counted, and not everything that can be counted counts”

-Albert Einstein

INTRODUCTION Qualitative research methods have become increasingly important as ways of developing

nursing knowledge for evidence-based nursing practice. Qualitative research answers a wide variety of questions related to nursing's concern with human responses to actual or potential health problems. (Ploeg J, 1999)

Qualitative research is a type of scientific research which has its roots in philosophy and human sciences.

Qualitative research plays an important part in providing evidence for practice in nursing, and is gaining greater acceptance within medicine. (Bailey C, 2002)

Definition: "A quantitative approach is one in which the investigator primarily uses post-positivist claims for developing knowledge (i.e. cause and effect thinking, reduction to specific variables and hypotheses and questions, use of measurement and observation, and the test of theories)." (Creswell, 2003)

Qualitative research is used to gain insight into people's attitudes, behaviours, value systems, concerns, motivations, aspirations, culture or lifestyles.

Qualitative researchers aim to gather an in-depth understanding of human behavior and the reasons that govern such behavior.

Qualitative research is often associated with naturalistic inquiry. Naturalistic methods of inquiry attempt to deal with the issue of human complexity by

exploring directly. Naturalistic inquiry always takes place in the natural settings (field). Naturalistic studies result in rich, in-depth information that has the potential to elucidate

the multiple dimensions of complicated phenomenon. The qualitative method investigates the why and how of decision making, not just what,

where, when. The qualitative researcher is interested in illumination and understanding rather than

causal determination or prediction.

DIFFERENCE BETWEEN QUALITATIVE AND QUANTITATIVE RESEARCH The key difference between quantitative and qualitative methods is their flexibility. In qualitative

methods, the relationship between the researcher and the participant is often less formal than in quantitative research

Quantitative Research Qualitative Research

General framework Seek to confirm hypotheses Postivist paradigm

Seek to explore phenomena Naturalistic paradigm

Objectives To predict & control To understand (what, how, & why)

Tools

Highly structured methods: questionnaires, surveys, and structured observation

Use semi-structured methods: in-depth interviews, focusgroups, and participant observation

Design Rigid design Controlled & experimental

Emergent design

Focus

Prediction Outcomes Generalisability

Rich “thick” description Similarities & contrasts Process & context

Nature of data analysis Statistical Non-statistical

Sampling Relatively large samples using

often random sampling Small samples using purposive, convenient or

snaw ball sampling technique.

METHODS OF COLLECTING DATA

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Obtrusive

Semi structured interviews In-depth interviews Focus Group Discussions Ethnography Participatory Action Research Narrative and Life History Participant observation

Unobtrusive methods Simple observation Document analysis (written records) Audio-visual Text analysis / Discourse analysis Material culture Auto-ethnography (object, subject and researcher)

Observation Most intuitive method

Three most common methods are Participant observation

o appropriate for collecting data on naturally occurring behaviors in their usual contexts.

In-depth interviewso optimal for collecting data on individuals’ personal histories, perspectives, and

experiences, particularly when sensitive topics are being explored. Focus groups

o effective in eliciting data on the cultural norms of a group and in generating broad overviews of issues of concern to the cultural groups or subgroups represented.

SAMPLING IN QUALITATIVE RESEARCH

Sampling methods used in qualitative research are:1. purposive sampling2. quota sampling, and3. snowball sampling

Purposive samplingo most common sampling strategy.o according to preselected criteria relevant to a particular research questiono Sample sizes depend on the resources and time available, as well as the study’s

objectives. Quota sampling

o In quota sampling, researcher decides while designing the study how many people with which characteristics to include as participants.

o Characteristics such as age, place of residence, gender, class, profession, marital status, use of a particular contraceptive method, HIV status, etc. are taken as inclusion criteria.

o The criteria chosen by the researcher allow him to focus on people he thinks would be most likely to experience, know about, or have insights into the research topic.

Snowball samplingo Also known as chain referral sampling.o In this method, participants or informants with whom contact has already been

made use their social networks to refer the researcher to other people who could potentially participate in or contribute to the study.

o E.g. To study a population of opium dependents, the researcher establishes a few contacts initially and these contacts help the researcher to get in contact with other members in the group.

PURPOSE OF QUALITATIVE RESEARCH

The purpose of qualitative research is to describe, explore, and explain phenomena being studied.

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Qualitative research questions often take the form of what is this? or what is happening here? and are more concerned with the process rather than the outcome. ( Ploeg J, 1999)

For better understanding of a phenomenon and gain new perspectives Collect and explore in-depth information that can’t be conveyed quantitatively. Provide rich descriptions of complex phenomena. Explore sensitive topics Explore the issues of difficult to access groups / subcultures Explore culturally defined experiences Track unique / unexpected events Illuminate experience and interpretation by actors Gives voice to those rarely heard

CHARECTERISTICS Takes place in the natural setting Uses multiple methods that are interpretive Is emergent rather than tightly prefigured Fundamentally interpretive (role of researcher as interpreter) Researcher views social phenomena holistically Researcher systematically reflects on who he or she is in the inquiry and is sensitive to hiw

or her personal biography and how it shapes the study Researcher uses complex reasoning that is multifaceted, iterative, and simultaneous Researcher adopts and uses one or more strategies of inquiry.

ETHICAL PRINCIPLES Respect for persons Beneficence Justice Respect for communities

PROCESSES IN QUALITATIVE RESEARCH Conceptualizing and planning

o Generally begin with a broad area to be studied.o Identify a site for data collection.o Make preliminary contactswith key actors in the selected site to ensure cooperation

and access to informantso In qualitative research, the research design is often referred to as emergent design-

a design that emerges during the course of data collection.o Adiotaping or videotaping interviews with informants

Conducting the qualitative studyo Data collectiono Data analysiso Interpretationo These processes take place in an interactive fashion.o The investigator starts data collection by talking with or observing a few people

who have first-hand experience of the phenomenon under study.o The analysis of qualitative data is an intensive and time-consuming task.o As the ananlysis and interpretaion progress, the researcher identify themes and

categories, which are used to build a descriptive theory of the phenomenon.o The guiding principle in deciding the sample size is data saturation.o Qualitative research reports are increasingly being published in nursing journals.o Qualitative finding are used as the basis for the formaulation of hypothesis that are

tested by quantitative research.

ANALSYING DATA IN QUALITATIVE RESEARCH Methods Interpretive techniques Coding Recursive abstraction Content analysis

Steps1. Organize and prepare the data for analysis2. Read all data, get a sense of the whole

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3. Begin detailed analysis with coding process4. Generate a description of the setting/people as well as categories or themes for analysis5. Identfy themes (writing, visual, etc.)6. Interpret and make meaning out of data

TYPES OF QUALITATIVE RESEARCH

Ethnography Ethnography is a description and interpretation of a cultural or social group or system. The research examines the group’s observable and learned patterns of behaviour, customs,

and ways of life. A picture of the “way of life” of some identifiable group of people Ethnography is closely related to Anthropology Its process include “doing fieldwork” and “going native” The focus of ethnography is with culture, and how people interact

with each other. Its is a both a research process and a product Methods include

o Direct observationo Participant observationo Unstructured Interview

Research Processo The ethnographer is the primary research instrumento The researcher spends one year or more in the field setting long enough to see a full

cycle of activityo For example, a full school yearo Emic and etic perspectives

Outsider’s broad and analytical perspective on groupstudied

Insider view, familiarity, empathy, identification withgroup

Phenomenology Phenomenology describes the subjective reality of an event, as perceived by the study

population; it is the study of a phenomenon. Phenomenological research techniques offer nurses a valuable way to understand the

lifeworld of nursing (Walters AJ) Analysis /description of everyday life Method

o InterviewSymbolic Interactionism

Making sense of experience via symbols Symbols find meaning through and in interaction Closely related to Grounded theory Method

o Semiotic analysisGrounded Theory

Grounded theory  is an inductive type of research, based in the observations or data from which it was developed

It uses a variety of data sources, including quantitative data, review of records, interviews, observation and surveys.

Concepts are basic units of analysis Concepts grouped and related to form abstract categories Relationships between categories identified to develop “formal theory” Theory building- concepts, categories, themes are identified and developed

during the study. Methods

o Interviewo Constant comparison

CRITICISMS

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The issue in qualitative research is validity /credibility / dependability.o Measures of establishing validity-member check, interviewer corroboration, peer

debriefing, prolonged engagement, negative case analysis, auditability, confirmability, bracketing, and balance

Rigor in qualitative researcho Triangulation is one way of promoting rigour in qualitative research. The term

refers to the use of more than one method of data collection and can involve triangulation of data, investigators and theories.

CONCLUSION

Qualitative research must be systematic, rigorous and planned to make it credible and dependable. It involves critical self-scrutiny (active reflexivity) to produce explanations. Such investigations

produce social explanations which are somewhat generalizable. Qualitative research is still not be seen as a unified body and face many criticisms.

REFERENCES:

1. Ploeg J. Identifying the best research design to fit the question. Part 2: qualitative designs. Evid Based Nurs 1999;2:36-37

2. Bailey C, Froggatt K, Field D, Krishnasamy M. The nursing contribution to qualitative research in palliative care 1990-1999: a critical evaluation. J Adv Nurs. 2002 Oct;40(1):48-60.

3. Strauss, Corbin. Basics of Qualitative Research: Grounded Theory Procedures and Techniques. Sage, Newbury Park, 1990.

4. Creswell, J.W.Research design.  Qualitative, quantitative and mixed methods approaches.  Thousand Oaks, CA: Sage, 2003.

5. Denzin & Lincoln (eds.). Handbook of Qualitative Research, 2ND ed., Sage Publications, Inc. London, 2000.

6. Polit H, Beck C T. Nursing research. 8th ed. New Delhi: Williams and Wilkins; 2008.7. Walters AJ. Phenomenology as a way of understanding in nursing, Contemporary Nurse

Journal;1994, 3:3-  134 - 141.

Journals on Qualitative Research1. Advances in Nursing Science 2. Holistic Nursing Practice 3. Journal of Advanced Nursing 4. Journal of Family Nursing 5. Nursing Research 6. Nursing Science Quarterly

Selected Published Artciles on Qualitative Research in Nursing

1). Anthony S, Jack S. Qualitative case study methodology in nursing research: an integrative review. J Adv Nurs. 2009 Jun;65(6):1171-81

This paper is a report of an integrative review conducted to critically analyse the contemporary use of qualitative case study methodology in nursing research in the context of increasing complexity in health care and increasing use of case study in nursing research. A sample of 42 case study research papers were analyzed using Whittemore and Knafl's integrative review method. It was summarised that confusion exists about the name, nature and use of case study and this methodology, including terminology and concepts, is often invisible in qualitative study titles and abstracts, despite its high quality exists in nursing research. The reviews conclude that judicious selection and diligent application of literature review methods promote the development of nursing science. Case study is becoming entrenched in the nursing research lexicon as a well-accepted methodology for studying phenomena in health and social care, and its growing use warrants continued appraisal to promote nursing knowledge development. Attention to all case study elements, process and publication is important in promoting authenticity, methodological quality and visibility.

2). Graneheim UH, Lundman B. Qualitative content analysis in nursing research: concepts, procedures and measures to achieve trustworthiness. Nurse Educ Today. 2004 Feb;24(2):105-12.

This paper provides an overview of important concepts (manifest and latent content, unit of analysis,

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meaning unit, condensation, abstraction, content area, code, category and theme) related to qualitative content analysis; illustrates the use of concepts related to the research procedure; and proposes measures to achieve trustworthiness (credibility, dependability and transferability) throughout the steps of the research procedure. Interpretation in qualitative content analysis is discussed in light of Watzlawick et al.'s  theory of communication.

3). DeSantis L, Ugarriza DN. The concept of theme as used in qualitative nursing research.West J Nurs Res. 2000 Apr;22(3):351-72.

 This literature review of qualitative research methodology and nursing research studies reveals considerable diversity in the identification of themes, the interpretation of the concept, and its function in data analysis. Part of the problem is the transfer of research methods from other disciplines to the study of nursing phenomena. The transfer often results in a blending of distinct research methods that compromises methodological rigor in data analysis and theory generation. A definition of theme is developed from the literature review and interdisciplinary definitions and descriptions. Five aspects of a theme and criteria foundational to the definition and concept of theme are identified. Implications of the concept of theme are presented for the conduct and application of research findings to the practice and development of nursing science.

4). Chen HY, Boore JR. Using a synthesized technique for grounded theory in nursing research. J Clin Nurs. 2009 Aug;18(16):2251-60.

Nursing increasingly uses grounded theory for a broadened perspective on nursing practice and research.  Authors suggested, nursing researchers intent on using a grounded theory methodology should pay attention to the theoretical discussions including theoretical sampling, theoretical sensitivity, constant comparative methods and asking questions, keeping memoranda diagramming, identification of a core category and a resultant explanatory theory.  Authors introduce a newly synthesized approach which may provide a true reflection of Glaser's idea of 'emergence of theory from the data' and Strauss and Corbin's style of sampling and memoranda writing is employed.

5). Pale J. Husserl, phenomenology and nursing. Journal of Advanced Nursing 2008; 26:1.

This study focuses on Husserl, and examines the relationship between his phenomenology and the accounts of it that are to be found in the nursing literature. Three central ideas were given particular attention: the phenomenological reduction, phenomena, and essence. It was argued that nurse researchers largely misunderstand these concepts and that, as a result, their version of Husserl's philosophy bears little resemblance to the original. Similarly, the project of identifying the 'essential structure' of a phenomenon, typically adopted by the nurse researchers who cite Husserl as an authority, comes close to being unintelligible. The author states that while the methods used in 'phenomenological' nursing research may still have some legitimacy, they cannot achieve what they are alleged to achieve, and they should be detached from the framework of Husserlian ideas and terminology which is supposed to justify them.

 

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Action Research in Nursing“There is no research without action; and there is no action without research”

-Kurt LevinIntroductionAction research is a process of gaining information about a situation through a deliberate processof: Making explicit assumptions about how and why things work  Planning to act to improve Carrying out the intervention that has been planned Observing what happens as a result of the intervention Reflecting on the observations Planning another intervention based on the reformulated hypothesis

“Action research is not merely research which it is hoped will be followed by action! It is action which is intentionally researched and modified leading to the next stage of action which is then again intentionally examined for further change and soon as part of there search itself”. -Yoland Wadsworth.

Action research is a reflective process of progressive problem solving led by individuals working with others in teams or as part of a "community of practice" to improve the way they address issues and solve problems. Action research can also be undertaken by larger organizations or institutions, assisted or guided by professional researchers, with the aim of improving their strategies, practices, and knowledge of the environments within which they practice.

Kurt Levin, a professor at MIT, first coined the term “action research” in about 1944. He described action research as “a comparative research on the conditions and effects of various forms of social action and research leading to social action” that uses “a spiral of steps, each of which is composed of a circle of planning, action, and fact-finding about the result of the action”.

Action Research and Nursing

Action research has gained popularity in Nursing and Health Care Research offering a way of developing practice-based knowledge, which can assist in changing practice and democratising inquiry. Modern health practice expects individual practitioners to develop patient focused, accessible, evidenced based services in diverse organisational settings. These situations occurs where the shifting boundaries between and within the nursing profession demands the need for practitioners to demonstrate their capacity as knowledgeable actors as they meet service delivery needs and empower their patients

Aim of action research is to build the capability of individuals and organizations to move beyond current conditions and practice. Recognized as a powerful tool for improving practice and the health of the organization.

Principles of Action Research1. Reflection

2. Dialogue 3. Collaboration 4. Risk 5. Multiple action and interpretation 6. Transformation (Theory and Practice)

Types of Action Research Traditional action research Contextual action research Radical action research Educational action researchRole of the Action Researcher Planner Designer Leader Observer

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Catalyser Reporter Teacher Listener Synthesizer Facilitator

Methods

The systematic process of inquiry available through action research extend the professional capacities of health practitioners, providing methods that improve the effectiveness and intervention that augment professional practice in ways that enhance outcome for clients. Acton Research involves:

Real situation, rather than contrived or experimental studies Primary focus is solving real problems Circumstances require flexibility Change must take place quickly or holistically People who wish to improve understanding of their practice

 

A multidimensional Model of Action Research

The Action Research sequence focuses on:

1. Change: Improving practices and behaviours by changing them. 2. Reflection: People’s thinking and reflecting, theorizing about their practices,

behaviours and situation. 3. Participation: People change their own practices and behaviours, not those of

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others. 4. Inclusion: Starting with agenda’s and perspectives of the least powerful, widening

the circle to include all those affected by the problem. 5. Sharing: People sharing their perspectives with others. 6. Understanding: Achieving clarity of understanding of the different perspectives and

experiences of all involved. 7. Repetition: repeating cycles of research activity leading towards solution to a

problem. 8. Practice: Testing emerging understanding by using them as the basis for

constructing new practice. 9. Community: Working towards the development/building of a learning community.

Action research is a collaborative approach Through its participatory process it enables the participants to

Investigate systematically their problems and issues Formulate powerful and sophisticated accounts of their situation and Devise plans to deal with the problems at hand

THE LEARNING CYCLE: THE CORE OF ACTION RESEARCH Elements

Reflecting on the current situation Planning a change to improve the situation Acting and observing the process and consequences of the change Reflection and preplanning the same

Action Research Cycle

Action Research is cyclical in nature since research participants continuously through processes of investigation as they work towards effective solutions to their research problem.

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The Look- Think-Act cycle signals that research participants will use new understandings emerging from data analysis to enhance or change their work practices- to take appropriate “action”. The act phase of the Look-Think-Act cycle of action research applies the knowledge and understandings emerging from research inquiry.

Benefits of Action Research

Creates a system wide mindset for improvement –a professional problem-solving process.

Enhances decision making –greater feelings of competence in solving problems and making instructional decisions. In other words, action research provides for an intelligent way of making decisions.

Promotes reflection and self-assessment Instils a commitment to continuous improvement Impacts directly on practice Empowers those who participate in the process

TWO APPROACHES TO ACTION RESEARCH

Qualitative Quantitative

QUALITATIVE RESEARCH

An inquiry process that explores a social or human problem, the researcher builds a complex, holistic picture, analyses words, reports detailed views of informants and conducts the study in natural setting-Creswell,1998

combines the scientific and artistic natures of nursing to enhance the understanding of

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human health experience. Involves broadly stated questions about human experiences and realities studied

through sustained contact with people in their natural environment Are concerned with answering questions such as what is ‘X’ ? and how does ‘X’ vary in different circumstances ? and why rather than how many X’s are there?

Qualitative research answers

 what has happened here rather than what is happening generally

METHODS OF QUALITATIVE RESEARCH

Ethnography Case study Grounded theory Phenomenological studies

1.  Ethnography

An ethnography is a description and interpretation of a cultural or social group or system. The research examines the group’s observable and learned patterns of behaviour, customs, and ways of life.

Leininger (1985) defined ethnography as the systematic process of observing, detailing, describing, documenting and analyzing the life ways or particular patterns of a culture

2. Case study

A case study is an exploration of a ‘bounded system’ … over time through detailed, in-depth data collection involving multiple sources of information rich in context. This bounded system is bounded by time and place, and it is the case being studied –a program, an event, an activity, or individuals

3. Grounded theory

Grounded theory studies are studies in which data are collected, analyzed and then a theory is developed that is grounded in the data.

Grounded theory is an important research method for the study of nursing phenomenon. The method explores the richness and diversity of the human experience and contributes to the development of middle range theories in nursing. It is an excellent method for understanding the processes through which patients learn to manage new or chronic health problems.

“Constructs and concepts are grounded in the data and hypotheses are tested as they arise from the research.” –(Field & Morse, 1985)

Systematic technique and process of analyzing the data through constant compression of data to identify pertinent concepts and interpret the data through intuitive process. –(Glaser & Strauss, 1967)

4. Phenomenological studies

Respondents are asked to describe their experiences as they perceive them.  Their description can be either in written form or spoken form. First person account of the experiences of people who survived the terrible Tsunami

disaster is an example.

METHODS OF DATA COLLECTION

In-depth Interviews Focus groups Participant observation Video

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Document review, field notes Document review provides relevant background or information for a report or study. Field notes typically include a field diary which provides a record of the chronological

events and development of research as well as the researchers own reaction to feelings about and opinions of the research process.

CHARACTERISTICS OF QUALITATIVE RESEARCH

Takes place in the natural setting Uses multiple methods that are interpretive Is emergent rather than tightly prefigured Fundamentally interpretive (role of researcher as interpreter) Researcher views social phenomena holistically Researcher adopts and uses one or more strategies of inquiry Sampling technique is purposive Data analysis is non statistical-Data can be in the form of notes, ideas, photographs etc. Analyzed by identifying significant categories and classification of information

Action Research Tools (Common to Qualitative Research)

keeping a research journal data document collection and analysis participant observation recordings questionnaire surveys structured and unstructured interviews case studies

Ethical Considerations

Relevant people, authorities and committees are consulted and principles are accepted All participants must be allowed to influence work and given the choice of opting out The work must be visible and open to suggestion from others Permission is obtained before observing or examining documents Must accept responsibility of maintaining confidentiality

Conclusion

Action research has gained popularity in nursing and healthcare research, offering a way of developing practice-based knowledge, which can assist in changing practice and democratizing inquiry. (Reed J, 2005)

Action research has also been utilized in three domains of  education: teacher education and professional development; research on science learning; and curriculum development and implementation.

Reed J. in a paper suggested some of the principles of action research appear to offer much towards the development of a practice-rooted body of knowledge for nursing, unless some of the issues of ownership are resolved, it is unlikely to move beyond academic rhetoric.

Action Research Articles

Reed J. Using action research in nursing practice with older people: democratizing knowledge.J Clin Nurs. 2005 May;14(5):594-600.

This paper reports on an action research study which raised some questions about the processes of developing a sense of shared ownership in action research in a research environment which does not always have the appropriate mechanisms to support and sustain action research.

I. Introduction

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Evidence based practice, is the use of the best clinical evidence in making patient care decisions and such evidence typically comes from research conducted by nurses and other health care professionals. Research is systematic inquiry that uses disciplined methods to answer questions or solve problems.  Nursing research has experienced remarkable growth in the past three decades, providing nurses with an increasingly sound evidence base from which to practice. Yet many questions endure and much remains to be done to incorporate research based evidence into nursing practice. The authenticity of the research findings, need to be assessed by careful critical analysis as to broaden the understanding, determine evidence for use in practice and provide a background for conducting further study.

II. Definition of critique

1. A research critique is a careful appraisal of the strengths and weaknesses of the study

2. An intellectual research critique is a careful, complete examination of a study to judge its strengths, weaknesses, logical links, meaning and significance

3. The process of objectivity and critically evaluating a research report’s content for scientific merit and application to practice, theory or education.

III. Steps in conducting research critique

1. Read and critique the entire study. A research critique involves examining the quality of all steps of the research process

2. Examine the organization and presentation of the research report. A well prepared report is complete, concise, clearly presented and logically organized. It does not involve excessive jargon that is difficult for students and practicing nurses to read. The reference need to be complete and presented in a consistent manner.

3. Examine the significance of the problem studied for nursing practice. The focus of nursing studies needs to be on the significant practice problems if a sound knowledge base is to be developed for the profession.

4. Identify strengths and weakness of a study. All studies have strengths and weaknesses, so attention must be given to all aspects of the study.

5. Be objective and realistic in identifying the study’s strength and weaknesses. Be balanced in the critique. Try not to be overly critical in identifying a study’s weaknesses or overly flattering in identifying strengths

6. Provide specific examples of the strengths and weaknesses of a study. Examples provide evidence for your critique of the strengths and weaknesses of a study.

7. Provide a rationale for your critique. Include justifications for the critique and document ideas with sources from the current literature. This strengthens the quality of the critique and documents the use of critical thinking skills.

8. Suggest modifications for future studies. Modifications in future studies will increase the strengths and decrease the weaknesses identified in the present study.

9. Discuss the feasibility of replication of the study. Is the study presented in enough detail to be replicated?

10. Discuss the usefulness of the findings for practice. The

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findings from the study need to be linked to the findings of previous studies. All those findings need to be examined for use in clinical practice.

IV. Phases of research critique                                                  BACK TO TOP

Phases of research critique are described briefly here:

A. QUALITATIVE RESEARCH

When critiquing them, one must examine differences between the qualitative approaches like grounded theory, phenomenology, or ethnography. Five standards have been developed to evaluate qualitative studies:

1. Descriptive vividness:

The study purpose, significance and interpretations must be articulated in such detail and richness that the reader has the sense of personally experiencing the event and clearly understand the significance of the findings. The threats to descriptive vividness include:

1. Failure to include essential descriptive information2. Lack of clarity in description3. Inadequate interpretative/analytic skill (what is most

essential, characteristic and defining about a given phenomenon

Guidelines:

Was the significance of the study adequately described? Was the purpose of the study clearly described? Were the interpretations presented in a descriptive way that

illuminated more than the quotes did?

2. Methodological Congruence:

It requires knowledge of the methodological approach the researchers used and whether that approach was consistent with the philosophical basis of the study. Methodological excellence has four dimensions

a. Adequate documentation of the participants: Requires a detailed description of the study participants, rationale for why and how the participants were selected and a description of the context and location where the study was conducted. Threats include:

Failure to describe the participants in detail Failure to provide a rationale for selecting the participants Failure to describe the context or location of the study so

that others can determine if the findings are applicable to their setting.

b. Careful attention to the procedural approach:  How careful the researcher is in applying selected procedures for the study? To the extent possible the researcher must clearly state the steps that were taken to ensure that data were accurately recorded and the data obtained are representative of the data as whole. Examine the description of assumptions, the data collection process, role of

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researcher for threats to the procedural approach. Threats include

Failure to articulate the assumptions associated with the research

Failure to establish trust with the participants, open dialogue and a conversational approach to data collection.

Failure to ask appropriate questions that address the participant’s beliefs, experiences, values or perceptions.

Failure to adequately describe the data collection process Failure to spend adequate time gathering data or to conduct

multiple interviews Failure to describe the data collection procedures used by

multiple data collectors Failure to use appropriate process for selecting and gaining

access to participants Failure to detail the role of the researcher during the

interview process Failure to describe the qualitative expertise of the

researchers

Guidelines:

1. Did the researcher identify the philosophical or theoretical base of the study?

2. Were the assumptions underlying the study articulated? Were the assumptions and data collection procedures congruent?

3. Was adequate trust established with the participants? Was there an open dialogue with a conversational approach to data collection?

4. Were research questions articulated? Did the researcher ask questions that explore participant’s experiences, beliefs, values or perceptions?

5. Was the data collection process adequately described?6. Did the researcher spend sufficient time with participants

gathering data? Did the researcher conduct multiple interviews?

7. Was the approach of multiple data collectors similar?8. Was the method of selecting and gaining access to the

study participants reasonable?9. Was the role of the researcher during the interview process

described? Were the researcher’s qualitative credentials and expertise described?

c. Adherence to ethical standards: requires recognition and discussion by the researcher of the ethical implications related to the study. The report must indicate that the researcher took action to ensure that the rights of the participants were protected during the study. Examine the data gathering process and identify potential threats which include:

Failure to inform participants of their rights Failure to obtain informed consent from the participants Failure to protect participant rights

d. Auditability: The research report needs to be sufficiently detailed to allow a second researcher with a similar background and philosophical approach, using the original data and the decision trail, to arrive at conclusions similar to those of the

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original researcher. Threats:

Failure of the researcher to record the nature of the decisions made, the data on which they are based and the decision trail, rules for arriving at conclusions. Other researchers with a similar background and philosophical background are not able to arrive at similar conclusions after applying the decision rules to the data.

Failure to include enough participant quotes to support the findings. The interpretative statements developed do not correspond with the findings.

Failure to provide quotes that are sufficiently rich or detailed to allow judgments to be made. This flaw also has been described as not achieving saturation or redundancy in the data

Failure to provide specific examples of the phenomenon being investigated.

Guidelines:

1. Was the decision trial used in arriving at conclusions described in adequate detail? Can the findings be linked with the data?

2. Were enough participant quotes included to support the findings?

3. Were the data sufficiently rich to support the conclusions? Were the findings validated by data? Did the participants describe specific examples of the phenomenon being investigated?

3. Analytical and interpretative preciseness:

The analytical process involves a series of interpretations and transformations during which concrete data are transformed across several levels of abstraction. The outcome imparts meaning to the phenomenon under study. It requires that the researcher involve others in the interpretative process and present a meaningful picture of the phenomenon under study. Threats include:

Failure to present the findings in a way that yields a meaningful picture of the phenomenon under study.

Failure to return the findings to participants or experts in the area or to readers who determine if the results are consistent with common meanings and understandings.

Failure to involve two or more researchers in data analysis or to describe how disagreements about data analysis were handled.

4. Philosophical or theoretical connectedness:

Requires that the findings developed from the study be clearly expressed, logically consistent and compatible with the knowledge base of nursing. Study assumptions, methodological procedures and interpretative/analytic approach must be consistent with the philosophical or theoretical basis of the study. Threats are:

Failure to link data to nursing practice Failure to identify a philosophical or theoretical basis for

the study Failure to cite references for the philosophical or theoretical

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approach used Failure to link the philosophical or theoretical basis of the

study with the study assumptions, data collection procedures and analytical and interpretative approach.

Guidelines:

1. Was a clear connection made between the data and nursing practice?

2. Did the researcher identify the philosophical or theoretical basis for the study? Were citations provided for the philosophical or theoretical approach used?

3. Was the theoretical and philosophical basis of the study consistent with the study assumptions, data collection process and analysis and interpretative methods used? Were citations provided for the philosophical or theoretical approach used?

5. Heuristic relevance:

It is reflected in the reader’s ability to recognize the phenomenon described in the study, its applicability to nursing practice and its influence on future research. The dimensions include:

a. Intuitive recognition: Readers immediately recognize the phenomenon, its connection to their personal experience and its relationship to nursing practice. Threat includes failure to present the findings in a way in which the reader can recognize them as being consistent with common meanings and experiences. Guidelines are:

Can the reader recognize the phenomenon described in the study?

Are the findings consistent with the common meanings or experiences?

b. Relationship to the existing body of knowledge: Similarities between the current knowledge base and the study findings add strength to the findings. The researcher needs to explore reasons for differences. Examine the degree to which the authors compared and contrasted the study findings with the results of other researcher’s work. Threats include:

Failure to examine existing body of knowledge Failure to compare and contrast the study findings with

those of other studies. Failure to describe the lacunae or omissions in current

understandings that would account for unique findings.

c. Applicability to nursing practice, research and education: In the discussion section examine implications of study findings and suggestions for future research. Threats include:

Failure to link study findings to nursing practice, research or education

Failure to emphasize how the findings extended what was previously reported in the literature

Failure to identify implications of the study for related cases

Failure to summarize suggestions for future research

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 B. QUANTITATIVE RESEARCH      

There are four critical thinking phases namely comprehension, comparison, analysis and evaluation. Comparison and analysis are done simultaneously.

1. Comprehension:

understanding the terms and concepts in the report, identifying the elements or steps of the research process such as problem, purpose, framework and design. It grasps the meaning, nature and significance of these steps. 

2. Comparison:

requires what each step of the research process should be like and then the ideal is compared to the real Examine the extent to which the researcher followed the rules of an ideal study.

3. Analysis:

Involves critique of the logical links connecting one study element with another. The steps of the research process need to be precisely developed and strongly linked to each other to conduct a quality study.

4. Evaluation:

The meaning and significance of the study are examined. The evaluation becomes a summary of the study’s quality that builds on conclusions reached during the first three phases. Guidelines are:

As the critique is on a quantitative study for the assignment, the guidelines are presented in detail below.

V. Guidelines for a quantitative   study critique:                  BACK TO TOP

I. Title:

Is the title a good one, succinctly suggesting key variables and the study population?

II. Abstract:

Does the abstract clearly and concisely summarize the main features (problem, methods, research conclusions)

III. Introduction                                                                         BACK TO TOP

I. Problem statement:

a. What is the study problem? Is it easy to locate?

b. Is the problem stated clearly and unambiguously? Is it easy to identify?

c.  Does the problem statement build a cogent and persuasive argument for the new study? Has the research problem been substantiated with adequate experiential and scientific background material?

d. Does the problem stated, expresses a relationship between two or more variables or at least between dependent and independent variable, implying empirical testability?

e.  Does the problem specify the nature of the population being studied?

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f. Does the problem have significance and relevance to nursing? Is the quantitative/ qualitative approach appropriate?

g. Is there a match between the research problem and paradigm and methods used?

h.  Is the problem sufficiently narrow in scope without being trivial?

i. Was this study feasible to conduct in terms of money commitment; the researcher’s expertise; availability of subjects, facility, equipment; ethical considerations?

j. Has the research problem been placed within the context of an appropriate theoretical framework?

k. Does the statement or purpose specify the nature of the population being studied?

ii. Purpose:

a.  What is the study purpose?

b.  Does the purpose narrow and clarify the focus or aim of the study and identify the research variables, population and setting?

c.  Is it worded appropriately? Are verbs used appropriately to suggest the nature of the inquiry and or the research tradition?

iii. Objectives:

a.   Formally stated? Clearly and concisely stated?

b.  Logically linked to purpose?

c.  Linked to concepts and relationships from the framework?

d.  Measurable or potentially measurable and achievable?

e.  Do they clearly identify the variables and population studied?

iv. Hypotheses:

Are they:

a.  Properly worded?

b.  Stated objectively without value laden words?

c.  Stating a predictive relationship between variables?

d.  Stated in such a way that they are testable?

e.  Directional or non directional/ research or statistical? Is the direction clearly stated? Are they causal, associative or simplex versus complex?

f.  Is there a rationale for how they were stated?

g.  Clearly and concisely expressed with variables and study population?

h.  Logically linked to the research problem and purpose?

i. Linked to concepts, relationships from the framework and literature review?

j. Used to direct the conduct of the study?

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k. Absent? If so is their absence justified? Are statistical tests used in analyzing the data despite the absence of stated hypothesis?

l. Derived from a theory or previous research? Is there a justifiable basis for the predictions?

m. Specific to one relationship so that each hypothesis can be either supported or not supported?

v.   Conceptual framework:

a. Is the study framework identified? Is a particular theory or model identified as a framework for the study?

b. Is the framework explicitly expressed or must be extracted from the literature review?

c. Does the absence of a framework detract from the usefulness or significance of the research?

d. Does the framework describe and define the concepts of interest or major features of the theory/ model so that readers can understand the conceptual basis of the study?

e. Does the framework present the relationships among the concepts?

f. Is a map or model of the framework provided for clarity? If a map or model is not provided, develop one that presents the study’s framework and describe it.

g. If there was an intervention, was there a cogent theoretical basis or rationale for the intervention?

h.  Is the theory or model used as the basis for generating hypothesis that were tested or is it used as an organizational or interpretive framework? Was this appropriate?

i. Is the theory/ model appropriate for the research problem? Would a different framework have been fitting?

j. Are deductions from theory are logical?

k. Links the concepts in the framework, with the variables in the study

l. Is the framework presented with clarity?

m. Are the concepts adequately defined in way that is consistent with the theory? If there is an intervention, are intervention components consistent with the theory?

n. Do the problem and hypothesis naturally flow from the framework? Or is the link contrived?

o. Is the framework related to nursing’s body of knowledge? Is it based on a conceptual model of nursing or a model developed by nurses? Is it borrowed from another discipline, is there adequate justification for its use?

p. Is the framework linked to the research purpose?

q. Is there a link between the framework, concepts being studied and the methods of measurement

r. If the proposition from a theory is to be tested, is the proposition clearly identified and linked to the study hypotheses?

s. Was sufficient literature presented to support study of the selected concepts?

t. Did the framework guide the study methods?

u. Does the researcher tie the findings of the study back to the framework at the end of the report? How do the findings support or undermine the framework? Are the findings interpreted within the context of the framework?

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vi. Variables

a. Do the variables reflect the concepts identified in the framework?

b. Are the variables clearly defined (conceptually and operationally) based on previous research and or theories?

c. Is the conceptual definition of a variable consistent with the operational definition? Do the theoretical definitions correspond to the conceptual definitions?

d. Are the variables that are manipulate or measured in the study consistent with the variables identified in the purpose or the objectives, hypothesis?

e. Are the major variables or concepts identified and defined (conceptually and operationally)? Identify and define the appropriate variables included in the study: Independent variables, Dependent variables, Research variables or concepts

f.  What attribute or demographic variables are examined in the study?

g. Were the extraneous variables identified and controlled as necessary in the study?

h. Are there uncontrolled extraneous variables that may have influenced the findings? Is the potential impact of these variables on the findings discussed?

I V. Review of literature                                                        BACK TO TOP

a.  Is the literature review presented? Does it reflect critical thinking?

b.  Are all relevant concepts and variables included in the review?

c. Are relevant previous studies (including, from other disciplines) identified and described?

d. Are relevant theories and models identified and described?

e. Are the references current? Examine the number of sources in the last five and ten years in the reference list.

f. Is the review thorough? Does it identify/uncover the gaps or inconsistencies in literature?

g. Is the review up-to-date?

h. Is it based on primary sources? Are secondary sources cited?

i. Provides a state of the art synthesis of evidence on the research problem?

j. Does it provide solid basis for the new study? Does the summary of the current empirical and theoretical knowledge provide a basis for the study

k. Are the studies critiqued by the author?

l. Is a summary of the current knowledge provided? This summary needs to include what is known and not known about the research problem.

m. Does the critique of each reviewed study include strengths, weakness, limitations of the design; conflicts; essential components of the design like size and type of sample, instruments its validity and reliability

n. Is the review well organized, flow logically, written concisely? Is the development of ideas clear to demonstrate the progressive development of ideas through previous research?

o. Is the review objective?

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p. Is there use of appropriate language?

q. If it is a review designed to summarize evidence for clinical practice. Does the review, draw appropriate conclusions about practice implications?

r. Is a theoretical knowledge base developed for the problem and purpose? Does it follow the purposes of the study?

s. Does the literature review provide a rationale and direction for the study?

t. Are both conceptual and data based literature included?

u. Is there a written summary synthesis of the reviewed scholarly literature?

v. Does the summary follow a logical sequence that leads reader to reasons why the particular research or non research project is needed?

V. Methodology:                                                                            BACK TO TOP

i. Ethical considerations:

a.  Are the rights of human subjects protected?

b. Were appropriate procedures used to safeguard the rights of study participants used?

c. Was the study subjected to an external review? Was the study approved and monitored by an institutional review board, research ethics board or other similar ethics review committee?

d. Was the study designed to minimize risks and maximize benefits to participants? Did the benefits outweigh any potential risks or actual discomfort they experienced?

e. Did the benefits to society outweigh the costs to participants?

f.  Was any undue coercion or undue influence used to recruit participants? Did they have the right to refuse to participate or to withdraw without penalty?

g. Were the study participants subjected to any physical harm, discomfort or psychological distress? Did the researchers take appropriate steps to remove or prevent harm?

h. Were participants deceived in anyway? Were they fully aware of participating in a study and did they understand the purpose and nature of research?

i. Were the subjects informed about the purpose and nature of the study?

j. Were appropriate informed consent procedures used with all subjects? Was the information essential for the consent provided? If not were there valid and justifiable reasons. Were the subjects capable of comprehending the information, competent to give consent? Did it seem that the subjects participated voluntarily?

k. Were adequate steps taken to safeguard the privacy of the participants. How data was kept anonymous or confidential? Was a certificate of confidentiality obtained?

l. Were vulnerable groups involved in the research? If yes, were special  precautions instituted because of their vulnerable status?.

m. Were groups omitted from the enquiry without a justifiable rationale?

n. Discuss the institutional review board approval obtained from University/agency where the study was conducted

ii. Design:                                                                         BACK TO TOP

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a. Is the research design clearly addressed? Identify the specific design of the study. Is the design employed appropriate?

b. Does the research question imply a question about the causal relationship between the independent and dependent variables?

c. What would be strongest design for the research question? How does this compare to the design actually used? Was the most rigorous possible design used, given the purpose of the research?

d. Does the researcher use the various concepts of control that are consistent with the type of design chosen?

e. Does the design seem to reflect the issues of economy?

f. What elements are controlled? What elements could have been controlled to improve the design?

g. What was the feasibility of controlling particular elements of the study? What was the effect of not controlling these elements on the validity of the study findings?

h. Were appropriate comparisons made to enhance interpretability of findings?

i. What elements of the design wee manipulated and how were they manipulated? How adequate was the manipulation? What elements should have been manipulated to improve the validity of findings?

j. Does the design used seem to flow from the proposed research problem, theoretical framework, literature review and the hypothesis?

k. What are the threats to internal and external validity?

l. What are the controls for the threats of internal and external validity?

m. Does the study include a treatment or intervention? If so is the treatment is clearly defined conceptually and operationally? Clearly described and consistently implemented? Was the control of comparison condition adequately explained? What justification from the literature provided for development of the experimental intervention? Was the intervention best that could be provided given current knowledge?

n. Does the study report, who implemented the treatment? If more than one person were they trained to ensure consistency in the delivery of the treatment? Was any control or comparison group intervention described?

o. Was there a protocol developed to ensure consistent or reliable implementation of the treatment with each subject throughout the study? Was an intervention theory provided to explain why the intervention causes the outcomes and exactly how the intervention produced the desired effects?

p. If experimental (or quasi) study, what specific experimental (or quasi) design was used? Were randomization procedures adequately explained? Is there adequate justification for failure to randomize subjects to treatment conditions? What evidence does the report provide that any groups being compared were equivalent before interventions?

q. If the study was non experimental, was the study inherently non experimental?  What was the design used? If retrospective, was there adequate justification for failure to use prospective design? What evidence does the report provide that any groups being compared were similar with regard to important extraneous characteristics?

r. If the study has more than one group, how were the subjects assigned to groups?

s. What type of comparisons are specified in the design (before-after, between groups)? Do these comparisons adequately illuminate the relationship between the independent and dependent variables? If there are no comparisons, or flawed comparisons, how does this affect the integrity of the study and the interpretability of the results?

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t. Was the study longitudinal? Was the timing of the collection of data appropriate? Was he number of data collection points reasonable?

u. Was masking and blinding used at all? If yes who was blinded and was this adequate? If not was there an adequate rationale for failure to mask? Is the intervention such that could raise expectation that in and of themselves could alter the outcomes? Did the design minimize biases and threats to the internal and external validity of the study?

v. Are the extraneous variables identified and controlled?

w. Were pilot study findings used to design the major study? Briefly discuss the pilot study and the findings. Indicate the changes made in the major study based on the pilot.

x. Is the design logically linked to the sampling method and statistical analyses?

y. Does the design provide a mean to examine all of the objectives, questions or hypothesis and the study purpose?

iii. Setting:

Discuss the setting and whether it was appropriate for the conduct of the study.

iv. Population and Sample:

a. Was the population identified and described? Was the sample described in sufficient detail? Is the target population to which the findings will be generalized defined?

b. Was the best possible sampling design was used to enhance sample’s representativeness? Were sample biases minimized? What was the possibility of type II error?

c. Is the sampling method adequate to produce a sample that is representative of the study population? Is the sample representative of accessible and target population?

d. Was the sample size adequate? Identify the sample size. Indicate if a power analysis was conducted to determine sample size

e. Identify the inclusion and exclusion sample criteria. Are the sample selection procedures clearly delineated?

f. Indicate the method used to obtain the sample. Did the researchers identify the sampling frame for the study?

g. Do the sample and population specifications support an inference of construct validity with regard to population construct?

h. What type of sampling plan was used? What alternative sampling plan have been preferable? Was it the one that could be expected to yield a representative sample?

i. How were subjects recruited into the sample? Does the method suggest potential biases?

j. Did some factor other than the sampling plan affect the representativeness of the ample?

k. Are possible sample biases or weaknesses identified? What are the potential biases in the sampling method

l. Is the sample sufficiently large to support statistical conclusion validity? Was the sample size justified on the basis of a power analysis or other rationale?

m. Does the sample support inferences about external validity? To whom can the study results reasonably be generalized?

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n. Are key characteristics of the sample described (female or male percentage, mean age etc.)

o. What number and percentage of the potential subjects refused to participate? Identify the sample mortality or attrition from the study. If so are justifications given?

p. If more than one group is used do the groups appear equivalent?

q. Have sample delimitations been established?

r. Would it be possible to replicate the study population? Does the researcher indicate how replication of the study with other samples would provide increased support for the findings?

v. Instrument/tools:                                                                        BACK TO TOP

a. Are all of the measurement strategies /instruments identified and described? Identify the author of each measurement strategy. Identify the type of each measurement strategy (Likert, visual analogue, physiological measurement, questionnaire, interview, observation). Is there rationale for their selection given?

b. Is the method used appropriate to the problem being studied? Were the methods used appropriate to the clinical situation? Are they similar for all subjects?

c. Identify the level of measurement (nominal, ordinal, interval or ration) achieved with each instrument. Discuss how each study instrument was developed.

d. Report the reliability and validity of each instrument or scale from previous studies and the current study. Discuss the precision and accuracy of the physiological measurement methods used in a study.

e. Was the set of data collection instruments adequately pretested?

f. Do the instruments adequately measure the study variables? Were key variables operationalized using the best possible method( e.g. interviews, observations and so on)  and with adequate justifications? Determine whether the type of measurement is direct or indirect.

g. Are the specific instruments adequately described in terms of reading level of questions, length of time to complete it, number of modules included and so on? Were they good choices, given the study purpose and study population? Was the mode of obtaining data was appropriate? (in person interview, mailed questionnaire, internet questioning)

h. Were self report data gathered in a manner that promoted high quality and unbiased responses( e.g. Privacy, efforts to put respondents at ease)

i. If observational data were used did the report adequately describe what specific constructs were observed? What was the unit of observation – was the approach molar or molecular?

j. Does the report provide evidence that data collection methods yielded data that were high on reliability and validity?

k. Are the instruments sufficiently sensitive to detect differences between subjects?

l. Is the validity and reliability of the instruments adequate for use in the study? Does the report offer evidence of the validity and reliability of measures? Does the evidence come from the research sample itself or is it based on other studies? If the latter is it reasonable to conclude that data quality would be similar for the research sample as for the reliability sample?

m. If validity and reliability is reported, which method of validity and reliability appraisal have been used? Was it appropriate? Is the reliability sufficiently high or the validity appear adequate? Should another method would have been used?

n. Do the instruments need further research to evaluate validity and reliability? If no information on validity and reliability, what conclusions can be reached on the quality of data?

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Scales and Questionnaires:

Are the instruments clearly described? Described well enough to know whether it covers the subject?

Are techniques to administer, complete and score instruments provided? Is the validity and reliability of the instruments described? Did the researcher examine the reliability and the validity of the instruments for the

present sample? If the instrument was developed for the study, is the instrument process development

described? Are the majority of the items appropriately close or open ended?  Is there a clear indication that the subjects understood the questionnaire? Is there evidence that subjects were able to perform the task? ·Observation: Is what is to be observed clearly identified and defined? Are interrater and intrarater reliability described? Are the techniques for recording observations described? Was there an observational guide? Is there any reason to believe that the presence of the observers affected the behavior of

the subjects? Were observations performed using the principles of informed consent? Was the researcher required to make inferences about what they saw?

Interviews:

Is the interview schedule described adequately enough to know whether it covers the subject?

Do the interview questions address concerns expressed in the research problem? Are the interview questions relevant for research purpose and objectives, questions or

hypotheses? Does the design of the questions tend to bias subject’s responses? Does the sequence of questions tend to bias subjects responses? Is there clear indication that the subjects understood the task and questions?

Physiological measure:

Are the measures or instruments clearly described? If appropriate are the brand names identified?

Is the instrument used appropriate to the research problem and forced to fit it? Is a rationale given for why a particular instrument was selected? Is there a provision for evaluating the accuracy of the instrument and those who use it? Are the accuracy, precision, selectivity, sensitivity, error of the physiological instruments

discussed? Are the methods for recording data from the physiological measures clearly described?

Available data and records:

Are the records used appropriate to the problem being studied? Are the data examined in such a way as to provide new information and not summarize

the records? Has the author addressed questions of internal and external criticism? Is there any indication of selection bias in the available records?

Focus groups:

What was the aim of the focus group? Was he group size appropriate for the focus group method? Was he group sufficiently homogeneous for its members to speak candidly? Was the moderator successful in keeping the discussion focused? Was the aim of the focus group achieved? Did the conclusions appear to be valid representation of the discussion?

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Were minority positions identified and explored?

Rating scale/ semantic differential scales/visual analogue scales:

Is the instrument clearly described? Are the techniques that were used to administer and score the scale provided? Is information about validity and reliability of the scale described from previous studies

or present sample? Was the instrument development process described, if scale was developed for the study?

vi. Data collection:

a. Did the researcher make the right decision about collecting new data versus existing data for the study?

b. Did the researcher make good data collection decisions with regard to structure, quantification, researcher obtrusiveness and objectivity?

c. Were the right methods used to collect the data? Was triangulation of methods used appropriately – were multiple methods used sensibly? Are the data collection procedures were same for all subjects?

d. Was the right amount of data collected? Were data collected to address the varied needs of the study? Were too many data were collected in terms burdening study participants? And is so how this might have affected data quality?

e. Did the researcher use good instruments, in terms of congruence with underlying constructs, data quality, reputation, efficiency and so on? Were new instruments developed unnecessarily?

f. Did the report provide adequate information about data collectors and data collection procedure? Is the data collection process clearly described?

g. Is the data collection process conducted in a consistent manner? Are the data collection methods ethical? Do the data collected address the research objectives, questions or hypotheses?

h. Who collected the data? Were data collectors judiciously chosen? Did they have traits that undermined the collection of unbiased, high quality data or did their traits enhance data quality?

i. Was the training of data collectors described? Was the training adequate? Were steps taken to improve the data collector’s ability to elicit or produce high quality data or to monitor their performance?

j. Where and under what circumstances were data gathered? Was the setting for data collection appropriate?

k. Were other people present during data collection? Could the presence of others have resulted in any biases?

l. Were data collected in a manner that minimized  bias? Did the intervention group did receive in intervention?

m. Was a category system or rating system used to organize and record observations? Were decisions about exhaustiveness and degree of observer inference appropriate?

n. What methods were used to sample observational units? Was the sampling approach good one? Did it likely to yield a representative sample of behavior? To what degree were observer biases controlled or minimized?  

o. Were biophysiologic measures used in the study and was this appropriate? Were appropriate methods used to measure the variables of interest? Did the researcher appear to have the skills necessary for proper interpretation of bio-physiologic measures?

VI. Data analysis.                                                                         BACK TO TOP

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a. Are data analysis procedures clearly described? What statistical analyses are included in the research report? Identify the analysis techniques used to describe the sample

b. Do data analyses address each objective, Question or hypothesis?

c. Are data analyses procedures appropriate to the type of data collected?

d. Are the results presented in an understandable way?

e. Are tables and figures used to synthesize and emphasize certain findings? Do the tables/ graphs figures used agree with the text and extend it or do they merely repeat it? Were the tables, graphs, pictures clear, with a good title, carefully labeled headings.

f.  Were appropriate descriptive statistics used? What descriptive statistics were reported? Do these statistics describe the major characteristics of the data set?

g. What level of measurement is used to measure each of the major variables? Were these descriptive statistics appropriate to the level of measurement of each variable?

h. Were any risk indexes computed? If not should they have been?

i. Is there appropriate summary statistics for each major variable?

j. Was the most powerful analytic method was used? Were type I and II errors were avoided or minimized?

k. Does the level of measurement and sample size permit the use of parametric statistics?

l. Are the statistics used appropriate to the problem, the hypothesis, the method, the sample and the level of measurement?

m. If non parametric tests were used was a rationale provided and does the rationale seem sound? Should more powerful parametric procedures have been used instead?

n. Are the results for each of the hypotheses presented appropriately? Are the tests that were used to analyze the data presented?

o. Is the information regarding the results presented, concise and sequential? Is the result interpreted in light of the hypotheses and theoretical framework an all the steps that preceded the results? Do the findings support the study framework?

p. Are the results clearly and completely stated? Presented objectively? Is there enough information to judge the results?

q. Was the level of significance or alpha identified? If so indicate the level. Identify the focus (description, relationship, differences) of each analysis technique, statistical procedures, test statistic, specific results, specific probability value in a table form

r.  Are significant and nonsignificant findings explained? If the results were nonsignificant, was the sample size sufficient to detect significant differences? Was a power analysis conducted to examine nonsignificant findings?

s.  Are the analyses interpreted appropriately? Does the interpretation of findings appear biased? Are the biases in the study identified?

t. Are there uncontrolled extraneous variables that may have influenced the findings? Do the conclusions fit the results from the analyses? Are the conclusions based on statistically and clinically significant results?

u. Were the statistically significant findings also examined for clinical significance? Is a distinction made between practical significance and statistical significance? How?

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v. What conclusions did the researcher identify based on this study and previous research? Are any generalizations made, how did the researcher generalize the findings? Are the generalizations within the scope of the findings or beyond the findings?

w. Are findings reported in manner that facilitates a meta-analysis and with sufficient information needed for evidence based practice? Are the findings adequately summarized?

VII. Discussion:                                                                         BACK TO TOP

a. What is the researcher’s interpretation of findings? Are all important results discussed? If not what is the likely explanation for omissions?

b. Did the researcher identify and discuss important study limitations and their effects on the results??

c. Are there inconsistencies of the report? Are the findings consistent with the results and with study’s limitations? Do the interpretations suggest distinct biases?

d. Are all major findings interpreted and discussed within the context of prior research and or the study’s conceptual framework? Are the findings consistent with previous research findings

e. Does the report address the issue of the generalizability of the findings? Are generalizations made that are not warranted on the basis of the sample used? Which findings are unexpected?

f. Are alternative explanations for the findings mentioned and is the rationale for their rejection presented?

g. Does the interpretation distinguish between practical and statistical significance? Are any unwarranted interpretations of causality made?

h. Do the researchers discuss the study’s implications for clinical practice, nursing education, nursing administration, nursing theory or make specific recommendations? What implications do the findings have for nursing practice? Are they reasonable and complete?

i. Are given implications appropriate given the study’s limitations and given the body of evidence from other studies? Are there important implications that the report neglected to include?

j. What suggestions/recommendations are made for further studies?

k. What are the missing elements of the study? Is the description of the study sufficiently clear to allow replication?

VII. Application and utilization:                                                      BACK TO TOP

a. How much confidence can be placed in the study findings? Are the findings an accurate reflection of reality? Do the study appear valid?

b. Are the findings related to the framework? Are the findings linked to those of previous studies? Are there other studies with similar findings? What do the findings add to the current body of knowledge? To what populations can the findings be generalized?

c. What research questions emerge from the findings? Are these questions identified by the researcher?

d. What is the overall quality of the study when strengths and weaknesses are summarized? Could any of the weaknesses have been corrected? Do the strengths outweigh the weaknesses?

e. Do the findings have potential for use in nursing practice? What risk/ benefit are involved for patients if the research findings would be used in practice?

f. Can the study be replicated by other researchers? Did the researcher use sound methodology? Do the findings accurately reflect reality? Are the findings credible?

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g. Is direct application of the research findings feasible in terms of time, effort money and legal and ethical crisis? How and under what circumstances are the findings applicable to nursing practice?

h. Does the study contribute any meaningful evidence that can be used in nursing practice or that is useful to the nursing discipline?

IX. Researcher credibility and presentation:                  BACK TO TOP

a. Does the researchers’ clinical, substantive or methodological qualifications and experience enhance confidence in the findings and their interpretation?

b. Is the report well written, well organized and sufficiently detailed for critical analysis? Is the report placed logical sequence and useful location?

c. Was the written in a manner that makes the findings accessible to practicing nurses?

VII. Conclusion:                                                                             

The exercise of a critique was a useful task to apply the knowledge of research. Identifying the strengths and weaknesses of the study including the constraints and limitations, helped to review the research process. The exercise gives a room for thoughtfulness and to hold the analysis in practical terms. Thus the research critique gives room for the authenticity of the information and to analyze the credibility of the findings and to weigh the evidence base in terms of practicality, objectivity, utilization, application and replication possibility.

VIII. References                                                                      

1. Polit H, Beck C T. Nursing research. 8th ed. New Delhi: Williams and Wilkins; 2008.2. Burns N, Grove S K. Understanding nursing research. 4th ed. New Delhi: Elsevier; 2007.   3. Wood G L, Haber J. Nursing research methods, critical appraisal and utilization.  5th ed. St

Louis: Mosby; 2002.4. Parahoo K. Nursing research.  2nd ed. New York: Palgrave; 2006.5. .Mateo M A, Kirchhoff K T. Using and conducting nursing research in the clinical setting. 2nd

ed. Philadelphia: W. B. Saunders company; 1999. 6. Talbot L A. Principles and practice  of nursing research. St. Louis: Mosby 1995.

Introduction to Biostatistics

-statistics are simply a collection of tools that researchers employ to help answer research questions

INTRODUCTION

Statistics plays a vitally important role in the research. Health information is very often explained in statistical

terms Many decisions in the Health Sciences are created through

statistical studies It enables you:

o to read and evaluate reports and other literatureo to take independent research investigationso to describe the data in meaningful terms

DEFINITIONS

1. Statistics: is the study of how to collect, organizes, analyze, and interpret data.

2. Data:  the values recorded in an experiment or

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observation.3. Population: refers to any collection of individual items or

units that are the subject of investigation.4. Sample: A small representative sample of a population is

called sample.5. Observation: each unit in the sample provides a record, as

a measurement which is called observation.6. Sampling: getting sample from a population7. Variable:  the value of an item or individual is called

variable8. Raw Data: Data collected in original form.9. Frequency: The number of times a certain value or class

of values occurs.10. Tabulation: can be defined as the logical and systematic

arrangement of statistical data in rows and columns.11. Frequency Distribution: The organization of raw data in

table form with classes and frequencies.12. Class Limits: Separate one class in a grouped frequency

distribution from another. The limits could actually appear in the data and have gaps between the upper limit of one class and the lower limit of the next.

13. Class Boundaries: Separate one class in a grouped frequency distribution from another.

14. Cumulative Frequency:  The number of values less than the upper class boundary for the current class. This is a running total of the frequencies.

15. Histogram: A graph which displays the data by using vertical bars of various heights to represent frequencies.

16. Frequency Polygon: it is a line graph. The frequency is placed along the vertical axis and the class midpoints are placed along the horizontal axis. These points are connected with lines.

17. Pie Chart: Graphical depiction of data as slices of a pie. The frequency determines the size of the slice. The number of degrees in any slice is the relative frequency times 360 degrees.

18. Central tendency - a typical or representative value for a dataset.

VARIABLES

The value of an item or individual is called variable. Variables are of two types:

o Quantitative: a variable with a numeric value. E.g. age, weight.

o Qualitative: a variable with a category or group value. E.g. Gender (M/F), Religion (H/M/C), Qualification (degree/PG)

Quantitative variable are two types:o Discrete /categorical variableso Continuous variables

32

Variables can beo  Independent

Are not influenced by other variables. Are not influenced by the event, but could

influence the event.o Dependent

The variable which is influenced by the others is often referred as dependent variable.

E.g. In an experimental study on relaxation intervention for reducing HTN, blood pressure is the dependent variable and relaxation training, age and gender are independent variable.

SAMPLING

Sampling is the process of getting a representative fraction of a population.

Analysis of the sample gives an idea of the population. Methods of sampling:

o Random Sampling or Probability sampling Simple random sampling Stratified random Sampling Cluster sampling

o Non-random sampling Convenient Sampling Purposive Sampling Quota Sampling

In Simple Random sampling, each individual of the population has an equal chance of being included in the sample. Two methods are used in simple random sampling:

Random Numbers method Lottery method In stratified random sampling, the population is divide

in to groups or strata on the basis of certain characteristics. In cluster sampling, the whole population is divided in to

a number of relatively small cluster groups. Then some of the clusters are randomly selected.

Convenience sampling is a type of non-probability sampling which involves the sample being drawn from that part of the population which is selected because it is readily available and convenient.

Purposive sampling is a type of non-probability sampling in which researcher selects participants based on fulfillment of some criteria. E.g. schizophrenia treatment naive.

33

SCALES OF MEASUREMENT

o Four measurement scales are used: nominal, ordinal, interval and ratio.

o Each level has its own rules and restrictions.

Nominal Scale of measurement

Nominal variables include categories of people, events, and other phenomena are named.

Example: gender, age-class, religion, type of disease, blood groups A, B, AB, and O.

They are exhaustive in nature, and are mutually exclusive. These categories are discrete and non-continuous.

o Statistical operations permissible are: counting of frequency, Percentage, Proportion, mode, and coefficient of contingency.

Ordinal Scale of measurement

It is second in terms of its refinement as a means of classifying information.

 It incorporates the functions of nominal scale. The ordinal scale is used to arrange (or rank) individuals

into a sequence ranging from the highest to lowest. Ordinal implies rank-ordered from highest to lowest.

Grade A+, A, B+, B, C+, C 1st , 2nd , 3rd etc

Interval scale of Measurement

Interval scale refers to the third level of measurement in relation to complexity of statistical techniques used to analyze data.

It is quantitative in nature The individual units are equidistant from one point to the

other. The interval data does not have an absolute zero.

E.g. temperature is measured in Celsius or Fahrenheit.

Ratio Scale of Measurement

Equal distances between the increments This scale has an absolute zero. Ratio variables exhibit the characteristics of ordinal and

interval measurement E.g. variable like time, length and weight

are ratio scales and also be measured using nominal or ordinal scale.

[The mathematical properties of interval and ratio scales are very similar, so the statistical procedures are common for both the scales.]

Introduction to Biostatistics

-statistics are simply a collection of tools that researchers employ to help answer research questions

34

PROCESSING OF DATA

The first step in processing of data is classification and tabulation. Classification is the process of arranging data on the basis of some

common characteristics possessed by them. Two approaches in analysing data are:

o Descriptive statisticso Inferential statistics

“Descriptive statistics are concerned with describing the characteristics of frequency distributions.” The common methods in descriptive analyses are:

o Measures of central tendencyo Measures of dispersiono Tabulation, cross-tab, contingency tableo Line diagram, bar diagram, pie diagram.o Histogram, frequency polygon, frequency curveo Quantile, Q-Q ploto Scatterplot

“The inferential statistics helps to decide whether the outcome of the study is a result of factors planned within design of the study or determined by chance.” Common inferential statistical tests are:

o T-testso Chi-squire testo Pearson correlation

Frequency Distribution

Simple depiction of all the data Frequency distribution is a statistical table containing “groups of

values according to the number of times a value occurs.” The data collected by an investigator is called raw data. Raw data is ungrouped data. It is not in order. Raw data is arranged in order called array. The data arranged in ascending order or descending order

Frequency Distribution with Classes

It is constructed with class intervals. It is a frequency distribution of continuous series. Raw data arranged as array data. Then the data is divided in to groups called classes. The first class and the last class are fixed by seeing the lowest and

highest values. Lowest and highest numbers of each class are called class limits

(upper & lower). The class limit may be made in two methods:

1. Inclusive methods2. Exclusive method

PRESENTATION OF DATA

1. Tabular presentation2. Diagrammatic Presentation3. Graphical Presentation

A. Tabular Presentation of Data

1. Arranging values in columns is called tabulation.1. E.g. The amount of oxygen content in water samples

35

Water samplesAmount of O2  in mL

1234

4.56.96.25.3

B.  Diagrammatic Presentation of data

1. It is a visual form of presentation of statistical data in which data are presented in the form of diagrams such as bars, lines, circles, maps

2. Advantages of diagrammatic presentation of data:1. It more attractive2. It simplify complex information3. It saves time4. It helps to make comparison.

3. Rules  for drawing diagrams1. It should have a title2. Proper scaling should be used.3. Index must be given for better understanding of diagrams

4. Common Types1. Line Diagram2. Pie diagram3. Bar diagram

Line diagram E.g. A traffic survey shows the following vehicles passing a particular bus stop during a hour

VehiclesFrequenc

yCarsLorriesMotor CyclesBuses

452263

Total 76

Pie Diagram

Example: blood group of 50 students

 Group   StudentsA             5B             20AB          10O             15

Bar Diagram

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Example: yield of various vegetables from a garden.

B. Graphical Presentation of data

1. Presenting data in the form of graphs prepared on a graph.2. The graph has two axes: X & Y3. Usually, Independent variable is marked on the X-axis and

dependent variable on the Y-axis.4. Common Types:

1. Histogram2. Frequency Polygon3. Frequency curve

Histogram

1. Histogram is a graph containing frequencies in the form of vertical rectangles.

2. It is an area diagram3. It is the graphical presentation of frequency distribution.4. X-axis is marked with class intervals5. Y-axis is marked with frequencies6. Histogram differs from bar diagram. The bar diagram is one

dimensional, whereas histogram is two-dimensional.7. Uses of histogram

1. It gives a clear picture of entire data2. It simplifies complex data3. Median and mode can be calculated.4. It facilitates comparison of two or more frequency

distributions on the same graph.

CategorySystolic

BP (mmHg)

Number of

Persons71 100-109 72 110-119 163 120-129 194 130-139 315 140-149 416 150-159 237 160-169 108 170-179 3

Frequency Polygon

37

     Frequency Curve

NORMALDISTRIBUTION

Normal distribution is a mathematical construct. It suggests naturally occurring observations follow a given

pattern. A normal distribution is bell-shaped and symmetric. The distribution is determined by the mean mu, and the standard

deviation sigma. The mean, mu controls the centre and standard deviation, sigma

controls the spread. A normal distribution curve is drawn by:

o  First drawing a normal curve.o Next, place the mean, mu on the curve.o Then place sigma on curve by placing the segment from

the mean to the upper (or lower) inflection point on your curve.

o From this information, the scale on the horizontal axis can be placed on the graph.

Normal distribution helps us to predict that where cases will fall within a distribution probabilistically.

o For example, what are the odds, given the population parameter of human height that someone will grow to more than eight feet?

o Answer: likely less than a .025 probability.

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For any normal curve with mean mu and standard deviation sigma:

o 68 percent of the observations fall within one standard deviation sigma of the mean.

o 95 percent of observation falls within 2 standard deviations.

o 99.7 percent of observations fall within 3 standard deviations of the mean.

o Mean = median = modeo The normal distribution has a skewness of zero.

Under most circumstances the mean, median, and mode will not be exactly the same.

Theoretically, two tails of the curve never touches the horizontal axis.

Skewness of distributions

Skewness is a measure of the asymmetry of the probability distribution.

If there is zero skewness (i.e., the distribution is symmetric) then the mean = median.

Skewness is of two types: Positive skewness: the right tail is longer; Its greatest frequency

occurs at a value near the left of the graph. It has relatively few high values. The distribution is said to be right-skewed. Example (observations): 1,2,3,4,100.

Negative skewness:  occurs at a value near the right of the graph. It has relatively few low values. The distribution is said to be left-skewed. Example (observations): 1, 1000, 1001, 1002, 1003.

Kurtosis

Kurtosis is the measure to explain whether the distribution may have high or low variance, even if normal.

The kurtosis value for a normal distribution will equal 3.Anything above this is a peaked value (low variance) and anything below is platykurtic (high variance).

39

Z-score

Z-scores are used to standardize the central tendency away from the mean across different samples.

The basic unit of the z-score is the standard deviation. The formula for calculating z-scores: any normal distribution

with mean=mu and standard deviation= sigma, can be converted into a standard normal Z distribution by the following transformation:

In the normal distribution, the z-score of 1.96 and 2.58 indicate the limits on either side of population mean within which 95percent  and 99 percent of all observations will fall.

PROBABILITY THEORY AND TEST OF SIGNIFICANCE

The probability theory arose from the study of games of chance (gambling).

Probability may be defined as quantifying the chance that a stated outcome of an event will take place.

Probability values fall on scale between 0 (impossibility) and 1 (certainty).

P= Number of nominated outcome/Number of possible outcome. Statisticians conventionally adopt three critical probability

values:o An outcome that is predicted to occur in less than 1 trial

in 20 (p<0.05) is considered to be unlikely or statistically significant.

o An outcome that is predicted to occur in less than 1 trial in 100 (p<0.01) is considered to be very unlikely or statistically highly significant.

o  An outcome that is predicted to occur in less than 1 trial in 1000 (p<0.001) is considered to be extremely unlikely or statistically very highly significant.

Standard Error or Random Sampling Error

Several small samples drawn from the same population generally provide different values of the same statistic, yet they are all estimates of the same population parameter. The variation between these individual estimates is called is due to

40

error. A statistical constant which measures the dispersion of the

sample means is around the total population mean is called standard error.

A sample statistic standard error is the difference between the mean of a sample and the mean of the population from which it is drawn.

The higher variance in the population also causes higher error in samples taken from it.

It is obtained by dividing standard deviation by the sample size. As the variance of the population increases, so does the chance

that a sample could not reflect the population parameters. The way in which sample statistics cluster around a population is

called sampling distribution. Random Sampling Error = standard deviation/ square root of the

sample size Formula for S.E.

Central Limit Theorem

If an infinite number of samples were taken from a population, the means of these samples would be normally distributed.

 Hence, the larger the sample relative to the population, the more likely the sample mean will capture the population mean.

Confidence Interval (CI)

We can actually use the information we have about a standard deviation from the mean and calculate the range of values for which a sample would have if they were to fall close to the mean of the population.

This range is based on the probability that the sample mean falls close to the population mean with a probability of error.

Social scientists use a 95% as a threshold to test whether or not the results are product of chance. are taken to be wrong.

The purpose of knowing about CI are:o CI interval is used for hypothesis testing.

Testing hypotheses

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Find a null and an alternative hypothesis  Example:

o – H0: Expected response is equal in both groupso – H1: Expected response is different between groups.

 p-value: is the probability to observe the observed values given that H0 is true.

Reject H0 if the p-value is less than a given significance level (e.g. 0.05 or 0.01)

DESCRIPTIVE STATISTICS

Measures of central tendancy Measures of dispersion/variability

MEASURES OF CENTRAL TENDANCY

A measure of central tendency is a single number used to represent the centre of a grouped data.

The basic measures are;o Mean, Median and Mode

For any symmetrical distribution, the mean, median, and mode will be identical.

Each measure is designed to represent a typical score. The choice of which measure to use depends on:

o the shape of the distribution (whether normal or skewed), ando the variable’s “level of measurement” (data are nominal,

ordinal or interval).

Mean

The mean (or average) is found by adding all the numbers and then dividing by how many numbers you added together.

Most common measure of central tendency. Formula for calculation of mean:

Best for making predictions. Applicable under two conditions: scores are measured at the distribution is more or less

Example:

3,4,5,6,7 3+4+5+6+7= 25 25 divided by 5 = 5 The mean is 5

Advantages of meano Mathematical center of a distribution.o Good for interval and ratio data.o Does not ignore any information.o Inferential statistics is based on mathematical properties of the

mean.

42

Disadvantages of meano Influenced by extreme scores and skewed distributions.o May not exist in the data.

Median

When the numbers are arranged in numerical order, the middle one is the median.

50% of observations are above the Median, 50% are below it. Formula Median = n + 1 / 2.

Example:

3,6,2,5,7 Arrange in order 2,3,5,6,7 The number in the middle is 5 The median is 5

Advantages:o Not influenced by extreme scores or skewed distribution.o Good with ordinal data.o Easier to compute than the mean.o Considered as the typical observation.

Disadvantages:o May not exist in the data.o Does not take actual values into account.

Mode

The number that occurs most frequently is the mode. We usually find the mode by creating a frequency distribution in which

we count how often each value occurs. If we find that every value occurs only once, the distribution has no

mode. If we find that two or more values are tied as the most common, the

distribution has more than one mode.

Example:

2,2,2,4,5,6,7,7,7,7,8 The number that occurs most

frequently is 7 The mode is 7

Advantages:o Good with nominal data.o Bimodal distribution might verify clinical observations (pre and

post-menopausal breast cancer).o Easy to compute and understand.o The score exists in the data set.

Disadvantages:o Ignore most of the information in a distribution.o Small samples may not have a modeo More than one mode might exist.

Appropriate Measures of Central Tendency

Nominal variables Ordinal variables

43

Interval level variables o If the distribution is normal (median is better with skewed

distribution)

MEASURES OF VARIABILITY

“If there is no variability within populations there would be no need for

Three indices are used to measure variation or dispersion among scores:

o rangeo variance, ando standard deviation (Cozby, 2000).

These indices answer the question: How Spread out is the distribution? Dispersion/Deviation/Spread tells us a lot about how a variable is

distributed.

Range

Range is the simplest method of examining variation among scores It refers to the difference between the highest and lowest values

produced. For continuous variables, the range is the arithmetic difference

between the highest and lowest observations in the sample. In the case of counts or measurements, 1 should be added to the difference because the range is inclusive of the extreme observations.

Another statistic, known as the interquartile range, describes the interval of scores bounded by the 25th and 75th percentile ranks; the interquartile range is bounded by the range of scores that represent the middle 50 percent of the distribution.

Percentiles (or quartiles)

The First quartile is the 25th percentile (noted Q1), the Median value is the 50th percentile (noted Median), and the Third quartile is the 75th percentile (noted Q3). ‘’ A percentile is a value at or below which a given percentage or

fraction of the variable values lie.” The p-th percentile is the value that has p% of the measurements below

it and (100-p)% above it. Thus, the 20th percentile is the value such that one fifth of the data lie

below it. It is higher than 20% of the data values and lower than 80% of the data values.’’

o E.g. if you are in the 80th percentile on a real GMAT result, you scored better on that section than 80% of the students taking the GMAT.

Standard deviation

The standard deviation is the most widely applied measure of variability.

It shows how much variation there is from the "average" (mean). Large standard deviations suggest that scores are probably widely

scattered. Small standards deviations suggest that there is very little deference

among scores. Computational formula for S.D:

44

Example: (Adapted from Wikipedia)

Consider a population consisting of the following values:

There are eight data points in total, with a mean (or average) value of 5:

To calculate the population standard deviation, first compute the difference of each data point from the mean, and square the result:

Next divide the sum of these values by the number of values and take the square root to give the standard deviation:

Therefore, the above has a population standard deviation of 2.

Variance

The squire of the standard deviation is the variance.

INFERENTIAL STATISTICS: COMMON TESTS

Chi-Squire Tests

o Chi-square test is designed to test for significant relationships between two variables organized in a bivariate table.

o Chi-square requires no assumptions about the shape of the population distribution from which a sample is drawn. However, like all inferential techniques it assumes random sampling.

o It can be applied to variables measured at a nominal and/or an ordinal level of measurement.

o The research hypothesis (variables are related in the population.

o The null hypothesis (between the two cross-tabulated variables in the population, and therefore the variables are statistically independent.

Formula for computing chi-squire statistic

45

Where, O=observed frequency, and

The essence of the frequencies with the frequencies expected for independence

o if the difference between observed and expected frequencies is large, then we can reject the null hypothesis of independence.

Determining the Degrees of Freedom

df = (r – 1)(c – 1)where, r = the number of rows and c = the number of columns

INFERENTIAL STATISTICS: COMMON TESTS

t-testsIndependent T-Test

t-test looks at the mean and variance of a sample of measurements, where the null hypothesis is that the sample is drawn from a distribution with mean m.

The test explains  the difference between the observed and expected means, scaled by the variance of the data, and tells us how likely one is to get a sample of that mean and variance, assuming that the sample is drawn from a normal distribution with mean mu..

Computational formula for independent t-test:

Conceptual model of independent t-test:

46

INFERENTIAL STATISTICS: COMMON TESTS

Correlation

Correlation

o Correlation refers to a type of statistic, to find out about a particular relationship between two variables.

o The correlation coefficient is written as o Correlation requires that both variables be quantitative.o Correlation Coefficient,

strength of the linear association between two numerical paired variables.

o Values range between –1 and +1 and measure the strength and direction of the relationship.

o A positive relationship exists when both variables increase and decrease at the same time. (Weight and height).

o A negative relationship exist when one variable increases and the other variable decreases or vice versa. (Strength and age).

o A scatter plot is used to explain the relationship between dependent and independent variable.

o By convention, the independent variable is plotted on the horizontal x-axis.the vertical y-axis.

o Independent variable: is a variable that can be controlled or manipulated.

o Dependent variable: is a variable that cannot be controlled or manipulated.the independent variable.

47

Strength of linear Relationship

r valueInterpretation

0 No correlation+1 Perfect positive linear relationship-1 Perfect negative linear relationship

Example

StudentABCDEF

1. Independent variable in this example is the number of hours studied.

2. The grade the student receives is a dependent variable.3. The grade student receives depend upon the number of hours he

or she will study.4. Are these two variables related?

48

1. Random Sampling or Probability sampling includes all the following techniques, except:

A. Simple random sampling

B. Stratified random Sampling

C. Cluster sampling

D. Purposive Sampling

Answer Key

2. Gender, age-class, religion, type of disease, and blood group are measured on:

A. Nominal scale of measurement

B. Ordinal scale of measurement

C. Interval scale of measurement

D. Ratio scale of measurement

Answer Key

3. Which scale of measurement has an absolute zero?

A. Nominal

B. Ordinal

C. Interval

D. Ratio

49

Answer Key

4. The variable which is influenced by the intervention of the researcher is called:

A. Independent

B. Dependent

C. Discrete

D. Extraneous

Answer Key

5. The statistical approach which helps the investigator to decide whether the outcome of the study is a result of factors planned within design of the study or determined by chance is called:

A. Descriptive statistics

B. Inferential statistics

C. Normal distribution

D. Standard deviation

Answer Key

6. Which of the following methods is a form of graphical presentation of data?

A. Line Diagram

B. Pie diagram

C. Bar diagram

D. Histogram

Answer Key

7. All the following are measures of central tendency, except:

A. Mean

B. Median

C. Mode

50

D. Variance

Answer Key

8. Which measure of central tendency is Influenced by extreme scores and skewed distributions?

A. Mean

B. Median

C. Mode

D. Range

Answer Key

9. A measure of central tendency which is calculated by numbers arranging in numerical order is:

A. Standard deviation

B. Range

C. Median

D. Mode

Answer Key

10. The proportion of observations fall above the median is:

A. 68%

B. 50%

C. 75%

D. 95%

Answer Key

11. The indices used to measure variation or dispersion among scores are all, except:

A. Range

B. Variance

C. Standard deviation

D. Mean

51

Answer Key

12. A measure of dispersion of a set of observations in which it is calculated by the difference between the highest and lowest values produced is called:

A. Standard deviation

B. Variance

C. Range

D. Mode

Answer Key

13. A statistic which describes the interval of scores bounded by the 25th and 75th percentile ranks is:

A. Inter quartile range

B. Confidence Interval

C. Standard deviation

D. Variance

Answer Key

14. The Median value is the:

A. 25th percentile

B. 50th percentile

C. 75th percentile

D. 95th percentile

Answer Key

15. Large standard deviations suggest that:

A. scores are probably widely scattered.

B. there is very little deference among scores.

C. mean, median and mode are the same

D. the scores not normally

52

distributed.

Answer Key

16. The formula given below is computational formula for:

A. Variance

B. Mean

C. Standard deviation

D. t-statistic

Answer Key

17. The squire of the standard deviation is the:

A. Variance.

B. Standard error

C. Z-score

D. Variance

Answer Key

18. Which is NOT a characteristic of normal distribution?

A. Symmetric

B. Bell-shaped

C. Mean = median = mode

D. Negative skewness

Answer Key

19. Skewness is a measure:

A. of the asymmetry of the probability distribution

B. decides the distribution may have high or low variance

53

C. of central tendency

D. None of the above

Answer Key

20. The formula given below is used to calculate:

O= Observed frequency

E= Expected frequency

A. t-test statistic

B. chi-squire statistic

C. correlation coefficient

D. Standard deviation

Answer Key

Answer Key

1. D 2. A

3. C

4. B

5.B 6. D

7. D

11. D

12. C

13. A

14. B

15. A

16. C

17. D

1. The variable in an experiment that is known from the start and does not change is called the:

A. dependent variable.

B. extraneous variable.

C. independent variable.

D. confounding variable.

Answer Key

2. Type I errors occur:

A. when the null hypothesis is rejected but it should have been retained.

B. accepting the null hypothesis when it should have been rejected.

C. considering the alternate hypothesis as

54

false when it actually it was true .

D. when the obtained p-value is higher than 0.05.

Answer Key

3. How many degrees of freedom would a table with 3 rows and 2 columns have?

A. 2

B. 1

C. 3

D. 4

Answer Key

4. Determining the Degrees of Freedom for a 2X2 contingency table for Chi-squire distribution is:

A. 4

B. 2

C. 0.05

D. 1

Answer Key

5. The degree of flatness or peakedness of a graph of a frequency distribution is termed as:

A. standard deviation

B. kurtosis

C. skewness

D.  mode

Answer Key

6. In a negatively skewed distribution, the mean generally falls to:

A. the left of the median and the median usually lies to the left of the mode.

B. the right of the median and the median usually

55

lies to the right of the mode.

C. the middle of median and mode.

D.  the centre of the distribution.

Answer Key7. Which statement about normal distribution is FALSE:

A. 50 percent of the observations fall within one standard deviation sigma of the mean.

B. 68 percent of the observations fall within one standard deviation sigma of the mean.

C. 95 percent of observation falls within 2 standard deviations.

D. 99.7 percent of observations fall within 3 standard deviations of the mean.

Answer Key8. A measure used to standardize the central tendency away from the mean across different samples is:

A. skewness

B. Range

C. Z-score

D. mode

Answer Key9. Probability values fall on scale between:

A. -1 to +1

B. 0 and 1.

C. -3 to + 3

56

D. 0.05 to 0.01

Answer Key

10. Standard error is calculated by:

A. dividing standard deviation by the square root of the sample size.

B. dividing number of nominated outcome by number of possible outcome.

C. adding all the numbers and then dividing by the numbers of observations.

D. arranging the numbers in numerical order, then taking the middle one.

Answer Key11. When explaining the direction of the linear association between two numerical paired variables, a positive correlation is stated when:

A. one variable increases and the other variable decreases or vice versa.

B. dependent variable increases and independent variable decreases

C. both variables increase and decrease at the same time.

D. correlation coefficient is stated close to 0.

Answer Key12. A type of graphical presentation data used to explain correlation between dependent and independent variable is:

A. Histogram

B. Frequency polygon

57

C. Frequency curve

D. Scatter plot

Answer Key

13. Correlation coefficient ranges from:

A. 0.01 to 0.05

B. 0 to 1

C. -1 to +1

D. -3 to +3

Answer Key

14. A contingency table (2x2) is used to calculate:

A. t-statistic

B. correlation coefficient

C. variance

D. chi-squire statistic

Answer Key15. The listed observations- 1,2,3,4,100, suggest the distribution:

A. is positively skewed

B. is negatively skewed

C. has zero skewness

D. is left-skewed

Answer Key16. 95% confidence interval refers to:

A. considering  1 out of 20 chances are taken to be wrong.

B. considering 1 out of 100 chances are taken as wrong.

C. considering 95 out of 100 chances are taken as wrong.

D. considering 5 out of 20

58

chances are taken as wrong.

Answer Key

17. A tentative explanation/statement of a declaration of the expected outcome of a research study based on observations is called:

A. Relationships

B. Analysis

C. Variables

D. Hypothesis

Answer Key

18. In a naturalistic observation, the phenomenon in which the behaviour of the subjects being observed changes because they are being watched is called:

A. Observer bias

B. Observer effect

C. participant observation

D. Representative sampling

Answer Key

19. The entire group of people or animals in which the researcher is interested is called:

A. Sample

B. Experiment group

C. Sample

D. Controls

Answer Key

20. In the scientific investigation, the first step is:

A. Reporting your results

59

B. Perceiving a question.

C. Drawing conclusion.

D. Testing hypothesis.

Answer KeyAnswer Key

1. C 2. A 3. A 4. D 5. B

6. A 7. A 8. C 9. B 10. A

11. C 12. D 13. C 14. D 15. A

16. A 17. D 18. B 19. C 20. B

1. Which of the following is NOT a method of quantitative research?

A. Grounded Theory Research

B. Correlational Research

C. Quasi-Experimental Research

D. Experimental Research

Answer Key

2. The term grounded theory was developed by

A. Heidegger

B. Glaser and Strauss

C. Husserl

D. Denzin

Answer Key

3. Deductive Reasoning is applied in:

A. Qualitative research

B. Quantitative research

C. Action research

D. Applied research

Answer Key

60

4. Which of the following is a qualitative research design where lived experiences of individuals are examined in their "life-world"?

A. Ethnography

B. Ethology

C. Phenomenology

D. Grounded theory

Answer Key

5. Which of the following is a characteristic of qualitative research?

A. Deductive process

B. Control over the context

C. Fixed research design

D. Inductive process

Answer Key

6. Qualitative research design involves

A. Emergent design

B. Correlative design

C. Experimental design

D. Cohort design

Answer Key

7. Phenomenological study involves all the following features, EXCEPT

A. Bracket out

B. Intuition

C. Analysis

D. Description

E. Manipulation

Answer Key

8. Which of the following qualitative methods focuses on description and

61

interpretation of cultural behavior?

A. Phenomenology

B. Grounded theory

C. Ethnography

D. Symbolic interactionism

Answer Key

9. The area of inquiry in grounded theory approach is

A. Holistic view of culture

B. Lived experiences

C. Behaviour observed over time in natural context

D. Social structural processes with in social setting

Answer Key

10. The research design in which the area inquiry is the manner by which people make sense of social interactions:

A. Grounded theory

B. Phenomenology

C. Symbolic interactionism

D. Ethnography

Answer Key

11. The term triangulation was coined by:

A. Denzin (1989)

B. Leininger (1985)

C. Glaser and Strauss (1967)

D. Heidegger

Answer Key

12. In qualitative research,

62

a guiding principle in deciding sample size is:

A. Effect size

B. Number of variables

C. Data saturation

D. Sub-group analysis

Answer Key

13. The term refers to the use of multiple referents to draw conclusions about what constitutes the truth:

A. Item analysis

B. Factor analysis

C. Error measurement

D. Triangulation

Answer Key

14. Characteristics of qualitative research design are

A. Flexible and elastic design

B. Use of mixed methodologies

C. Ongoing analysis to formulate subsequent strategies

D. Researcher becomes the instrument

E. All of the above

Answer Key

15. The tendency in qualitative research to derive a complex array of data from a variety of sources, using variety of methods is termed as:

A. Triangulation

B. Bricolage

C. Cross-tabulation

63

D. Confirmability

Answer KeyAnswer Key

1. A 2. B 3. B 4. C 5. D

6. A 7. E 8. C 9. D 10. C

11. A 12. C 13. D 14. E 15. B

1. Correlation coefficient provides all of the following information, except :

A. whether or not there is a relationship between the variables.

B. the strength of the relationship between the variables.

C. the cause of the relationship between the variables.

D. the direction of the relationship between the variables.

Answer Key

2. Another name for a bar graph is:

A. polygon

B. histogram

C. normal curve

D. line graph

Answer Key

3. A table that shows how often different scores appear in a set of scores is called a frequency:

A. polygon

B. histogram

C. normal curve

64

D. distribution

Answer Key

4. All the following are components required for estimating power (1-beta) of a study, EXCEPT

A. The population effect size

B. Sample size

C. Level of significance (alpha)

D. Standard deviation

Answer Key

5. Using power analysis (Cohen, 1977), the value of estimated effect size (gamma) for large effects in two group test of mean difference is

A. 0-2

B. 0.5

C. 0.8

D. 1.0

Answer Key

6. When doing power analysis in ANOVA context, the estimate of effect size is

A. Eta-squared

B. Correlation coefficient

C. Standard Error

D. Chi-squire value

Answer Key

7. Analysis of Variance (ANOVA) test is used to

A. Test the difference between two independent group means

B. Test the difference between two related group

65

means

C. Test the difference among the means of 3+ independent groups

D. Test the difference in ranks of scores of 3+ independent groups

Answer Key8. Kruskal-Wallis test is used to:

A. Test the difference between two independent group means

B. Test the difference among the means of 3+ related groups

C. Test the difference among the means of 3+ independent groups

D. Test the difference in ranks of scores of 3+ independent groups

Answer Key

9. Which is the most appropriate inferential analysis to test the difference among the means of 3+ related groups o sets of scores?

A. Repeated-measures ANOVA

B. Friedman test

C. Paired t-test

D. Wicoxon signed-rank test

Answer Key

10. Power analysis builds on the concepts of:

A. Validity

B. reliability

C. Internal consistency

66

D. Effect size

Answer Key

11. Effect size is used to calculate:

A. Reliability

B. Sample size

C. Internal consistency

D. Predictive validity

Answer Key

12. The F-statistic is calculated in:

A. ANOVA

B. T-test

C. Correlation analysis

D. Chi-squire test

13. Which of the following is a nonparametric "Analysis of Variance"?

A. Mann-Whitney U test

B. Wilcoxon Rank test

C. Kruskal-Wallis test

D. Friedman's test

14. Chi-square test is used to test:

A. Difference in proportions

B. Difference in means of two independent variables

C. Relationship between two bivariate variables

D. Difference in means of three or more set of variables

15. Which of the following

67

is NOT a criteria for Fisher's exact test?

A. When proportions derived from independent groups are compared

B. When there are cells with a value of 0

C. Sample size is small (less than 30)

D. When testing difference between three or more group means

Answer Key

1. C 2. B 3.D 4. D 5. C

6. A 7. C 8. D 9. A 10. D

11. B 12. A 13.C 14. A 15. D

1. The type of research focused on finding a solution to an immediate practical problem is termed as:

A. Basic research

B. Applied research

C. Explanatory research

D. Descriptive research

Answer Key

2. The principles of ethics in nursing research include:

A. Beneficence

B. Respect for human dignity

C. Justice

D. All of the above

Answer Key

3. Which of the following is TRUE about features of

68

quasi-experimental research design?

A. Manipulation. control group, randomization

B. Manipulation, but no control group or randomization

C. No manipulation of independent variable

D. Use of correlational approach

Answer Key

4. Carry-over effects are related to:

A. Factorial design

B. Pretest-posttest design

C. Solomon four-group design

D. Repeated measures design

Answer Key

5. The extent to which it is possible to make an inference that independent variable is truly influencing the dependent variable and relationship is not spurious, refers to:

A. External validity

B. Internal Validity

C. Internal consistency

D. Reliability

Answer Key

6. Which of the following is considered as a threat to internal validity of a research?

A. The Hawthorne effect

B. Novelty effect

C. Experimenter effects

69

D. Maturation

E. Measurement effects

Answer Key

7. Which of the following is NOT related to dealing with extraneous variables in a quantitative research?

A. Randomization

B. Repeated measures

C. Homogeneity

D. Blocking

E. Bracketing

Answer Key

8. Which of the following is a method of integrating the findings of prior research studies using statistical procedures?

A. Meta-analysis

B. Secondary analysis

C. Content analysis

D. Grounded theory

Answer Key

9. The term used to indicate the placebo effect in which the knowledge of being included in a study cause people to change their behaviours, thereby obscuring the variable of interest:

A. Internal validity

B. Maturation

C. Manipulation

D. Hawthorne effect

Answer Key

10. Investigations in which samples from a general population are studied over time with respect to some phenomenon is

70

termed as

A. Trend studies

B. Action research

C. Outcome research

D. Meta-anlysis

Answer Key

11. Which of the following data collection method has better subjectivity?

A. Self-reports

B. Observation

C. Biophysiologic measures

D. Questionnaires

Answer Key

12. Basic principles that are accepted as being true on the basis of logic or reason, without proof or verification is termed as:

A. Assumptions

B. Hypothesis

C. Constructs

D. Propositions

Answer Key

13. A fundamental ethical principle that seeks to prevent harm and exploitation of, to maximize benefits for, study participants is:

A. Justice

B. Beneficence

C. Nonmalificence

D. Coercion

Answer Key

14. A method of data collection in which several rounds of questionnaires are mailed to a panel of

71

experts, focusing on their opinions or judgment concerning a specific topic of interest is:

A. Focus group interview

B. Meta-analysis

C. Delphi technique

D. Secondary analysis

Answer Key

15. The principle of beneficence include all the following, EXCEPT

A. Freedom from harm

B. Freedom from exploitation

C. Benefits from research

D. Risk/benefit ratio

E. The right to self-determination

Answer KeyAnswer Key

1.B 2.D 3.B 4.D 5.B

6.D 7.E 8.A 9.D 10.A

11. C 12.A 13.B 14.C 15.E

1. The degree of consistency with which an instrument measures the attribute it is supposed to be measuring is called:

A. Validity

B. Reliability

C. Sensitivity

D. Objectivity

Answer Key

2. The reliability of a measuring tool has following aspects, except:

72

A. Stability

B. Internal consistency

C. Efficiency

D. Equivalence

Answer Key

3. The extent to which the same results are obtained on repeated administrations of the instrument is termed as:

A. Internal consistency

B. Validity

C. Stability

D. Sensitivity

Answer Key

4. The stability index of a measuring tool is derived through procedures that evaluate:

A. Interrater reliability

B. Internal consistency

C. Crombach's alpha

D. Test-retest reliability

Answer Key

5. The Spearman's-Brown formula is used to estimate:

A. Test-retest reliability

B. Internal consistency

C. Equivalence

D. Validity

Answer Key

6. The degree to which an instrument measures what it is supposed to be measuring is its:

A. Validity

73

B. Internal consistency

C. Sensitivity

D. Equivalence

Answer Key

7. Which of the following is NOT a type of validity index of a research instrument?

A. Predictive validity

B. Content validity

C. Concurrent validity

D. Construct validity

E. Homogenous validity

Answer Key

8. The adequacy of an instrument in differentiating between the performance or behaviour on some future criterion is termed as:

A. Predictive validity

B. Cocurrent validity

C. Content validity

D. Construct validity

Answer Key

9. Multi-trait-multi-matrix (MTMM) is a procedure developed to establish:

A. Internal consistency

B. Interrater reliability

C. Construct validity

D. Content validity

Answer Key

10. Which of the following is NOT a procedure for establishing construct validity of an instrument?

A. Known-group

74

technique

B. Factor analysis

C. MTMM

D. Crombach's alpha

Answer Key

11. The most common type of composite scale is:

A. Likert scale

B. Visual analog scale

C. Checklists

D. Thurstone scale

Answer KeyAnswer Key

1. B 2.C 3. C 4.D 5.B

6. A 7. E 8. A 9. C 10. D

11. A

1. The degree of consistency with which an instrument measures the attribute it is supposed to be measuring is called:

A. Validity

B. Reliability

C. Sensitivity

D. Objectivity

Answer Key

2. The reliability of a measuring tool has following aspects, except:

A. Stability

B. Internal consistency

C. Efficiency

D. Equivalence

75

Answer Key

3. The extent to which the same results are obtained on repeated administrations of the instrument is termed as:

A. Internal consistency

B. Validity

C. Stability

D. Sensitivity

Answer Key

4. The stability index of a measuring tool is derived through procedures that evaluate:

A. Interrater reliability

B. Internal consistency

C. Crombach's alpha

D. Test-retest reliability

Answer Key

5. The Spearman's-Brown formula is used to estimate:

A. Test-retest reliability

B. Internal consistency

C. Equivalence

D. Validity

Answer Key

6. The degree to which an instrument measures what it is supposed to be measuring is its:

A. Validity

B. Internal consistency

C. Sensitivity

D. Equivalence

Answer Key

7. Which of the following

76

is NOT a type of validity index of a research instrument?

A. Predictive validity

B. Content validity

C. Concurrent validity

D. Construct validity

E. Homogenous validity

Answer Key

8. The adequacy of an instrument in differentiating between the performance or behaviour on some future criterion is termed as:

A. Predictive validity

B. Cocurrent validity

C. Content validity

D. Construct validity

Answer Key

9. Multi-trait-multi-matrix (MTMM) is a procedure developed to establish:

A. Internal consistency

B. Interrater reliability

C. Construct validity

D. Content validity

Answer Key

10. Which of the following is NOT a procedure for establishing construct validity of an instrument?

A. Known-group technique

B. Factor analysis

C. MTMM

D. Crombach's alpha

Answer Key

11. The most common

77

type of composite scale is:

A. Likert scale

B. Visual analog scale

C. Checklists

D. Thurstone scale

Answer KeyAnswer Key

1. B 2.C 3. C 4.D 5.B

6. A 7. E 8. A 9. C 10. D

11. A

1. The term “action research” was coined by:

A. Kurt Lewin

B. Glaser & Strauss

C. Karl Pearson

D. Jacob Cohen

Answer Key

2. A careful appraisal of the strengths and weaknesses of the study is:

A. Research proposal

B. Action Research

C. Research critique

D. Evidence-based practice

Answer Key

3. The standards of critiquing qualitative research include, except:

A. Descriptive vividness

B. Methodological Congruence

C. Analytical and interpretative preciseness

78

D. Heuristic relevance

E. Chance for committing Type-I error

Answer Key

4. History as a threat to the internal validity of a particular study (Cook and Campbell) refers to:

A. An event that takes place between pretest and posttest.

B. Natural change during the period between baseline and posttest

C. Groups that are formed not on randomization bases.

D. The phenomenon of differential attrition during the course of treatment.

Answer Key

5. The phenomenon of those who obtain extreme scores at pretest tending to obtain less extreme scores at posttest, at both the high and low ends of the measure is:

A. Internal validity

B. Statistical regression

C. Statistical power

D. Statistical validity

Answer Key

6. The concept of statistical power in the social and behavioural sciences was first introduced by:

A. Carl pearson

B. Spearman

C. Jacob Cohen

79

D. Kolmogrov

Answer Key

7. The probability that a given effect will be detected using a sample of a specified size, with the probability level of the statistical test being set at a predetermined level: is

A. Power of a statistical test

B. Internal validity

C. External validity

D. Reliability of a study

Answer Key

8. . The four parameters of power analysis are, except:

A. The alpha or probability level of the significance test

B. The size of the effect hypothesized or to be detected.

C. The size of the sample being studied.

D. The power of the statistical test.

E. Reliability of the rating scale

Answer Key

9. The probability of making a Type II error in any statistical testis termed as:

A. Alpha

B. Beta

C. Gamma

D. Theta

E. Delta

Answer Key

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10. A pharmacology trial concluded that a new antipsychotic reduced negative symptoms when in reality it did not; is an example of:

A. Type I error

B. Type II error

C. Type III error

D. Type IV error

Answer Key

11. For a two-group comparison study, standardized measure of effect size is:

A. Square of the Pearson correlation coefficient.

B. Eta squired value

C. Chi-squire value

D. The difference between the two means, divided by the average of the standard deviations.

Answer Key

12. Kappa coefficient of reliability is related to:

A. Ratio scale of measurement

B. Interval scale of measurement

C. Nominal scale of measurement

D. Continuous variables

Answer Key

13. The sum of the values of a variable for a set of observations, divided by the number of the observations in the set refers to:

A. Variance

B. Standard deviation

81

C. Median

D. Mean

E. Mode

Answer Key

14. The degrees of freedom for the chi-square test is

A. ( R + 1) (C - 1 )

B. (R − 1) (C − 1)

C. (R - 1) (C + 1)

D. (R x C) - 1

Answer Key

15. Which of the following is NOT a multivariate statistical approach?

A. Analysis of covariance (ANCOVA)

B. Multiple Regression

C. Factor Analysis

D. Structural Equation Modeling

E. Analysis of variance

Answer KeyAnswer Key

1. A 2. C 3. E 4. A 5. B

6. C 7. A 8. E 9. B 10. A

11. D 12. C 13. D 14. B 15. E

1. Studies that produce basic estimates of the rates of disorder in a general population and its subgroups is:

A. Qualitative epidemiology

B. Analytic epidemiology

82

C. Experimental epidemiology

D. Descriptive epidemiology

Answer Key

2. The number of new cases that occur within a specific population within a defined time interval is:

A. Point Prevalence

B. Incidence

C. Period prevalence

D. Lifetime Prevalence

Answer Key

3. What is the Z-score for 97.5th percentile in a distribution?

A. +1.96

B. -1.96

C. +2.5

D. 0.05

Answer Key

4. The statistic used to explain the chances of being exposed to a risk among those with the diagnosis divided by exposure to the risk among those without the diagnosis is:

A. Phi coefficient

B. Odds ratio

C. Chi square

D. Kappa

Answer Key

5. The phi coefficient is used for correlations between

A. Two continuous variables

83

B. Two set of means

C. Two dichotomous variables.

D. Two rating scales

Answer Key

6. In biomedical research survival analysis is typically used to evaluate

A. Incidence of a disease

B. Point Prevalence

C. Life expectancy

D. Lifetime Prevalence

Answer Key

7. A systematic method for continuous monitoring of diseases in a population, in order to be able to detect changes in disease patterns and then to control them is:

A. Conditional probability

B. Screening

C. Prevalence

D. Surveillance

Answer Key

8. A hypothesis which a researcher tries to disprove is:

A. Research hypothesis

B. Null hypothesis

C. Alternate hypothesis

D. Positive hypothesis

Answer Key

9. In epidemiology research, If the relative risk is greater than 1.0, the group with the suspected risk factor:

A. have a lower incidence

84

rate of the disorder.

B. have a higher incidence rate of the disorder.

C. is having no relationship with the risk factor.

D. None of the above

Answer Key

10. Number of births divided by total population includes men women and children (1000s) is:

A. Crude birth rate

B. General fertility rate

C. Age-specific fertility rates

D. Total period fertility rate

Answer KeyAnswer Key

1. D 2. B 3. A 4. B 5. C

6. C 7. D 8. B 9. B 10. A

1. All of the following diagrams can be draw from quantitative data, except:

A. Frequency curve

B. Scatter diagram

B. Flow diagram

D. Histogram

Answer Key

2. In a community correlation between infant mortality and socioeconomic status is:

A. r = +1 (Strong positive

85

correlation)

B. r = -1 (strong negative correlation)

C. r = -0.8 (moderate negative correlation)

D. r = +0.22 (strong positive correlation)

Answer Key

3. Best graph for demonstration of relationship between ages and weight is:

A. Bar Diagram

B. Histogram

C. Scatter

D. Pie diagram

Answer Key

4. Age and sex representation is best represented by:

A. Histogram

B. Pie chart

C. Bar diagram

D. Sketch of photos

Answer Key

5. Quantitative data can be best represented by:

A. Pie chart

B. Pictogram

C. Histogram

D. Bar diagram

Answer Key

6. Percentage of data can be shown in:

A. Graph presentation

B. Pie chart

86

C. Bar diagram

D. Histogram

Answer Key

7. The average berth weights in a hospital are to be demonstrated by statistical representation. This is best done by:

A. Frequency curve

B. Pictogram

C. Histogram

D. Bar diagram

Answer Key

8. In a random sample taken for a population, the median is higher than:

A. 25

B. 50

C. 67

D. 100

Answer Key

9. For determination of which statistical parameter requires quantities to be arranged in an ascending or descending order?

A. Mean

B. Median

C. Mode

D. SD

Answer Key

10. In a population of 100 females in the age group of 15-45, the mean systolic BP was found to be 120. In a normal curve distribution, the number of people who would have an average BP above 120 will be:

87

A. 25

B. 50

C. 75

D. 95

Answer Key

11. The two important values necessary for describing the frequency distribution of a series of observation are:

A. Mean and standard deviation

B. Mean and range

C. Median and range

D. Median and standard deviation

Answer Key

12. Arrangement of values in a serial order is to determine:

A. Mean

B. Mode

C. Median

D. Range

Answer Key

13. A scatter diagram shows:

A. Trends of events with the passage of time

B. Relationship between two variables

C. Proportion of an event

D. Positive relationship between two variables

Answer Key

14. In 11 babies born in a hospital is 5 above 2.5 kg and 5 below 2.5 kg. The value 2.5 is:

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A. Median average

B. Mode average

C. Geometrical mean

D. Arithmetic average

Answer Key

15. Relationship between two variables can be presented by:

A. Pie diagram

B. Scatter diagram

C. Bar diagram

D. Histogram

Answer KeyAnswer Key

1. C 2. c 3. A 4. A 5. C

6. B 7. D 8. B 9. B 10. B

11. A 12. C 13. B 14. A 15. B

1. Calculate the median of trhese ten values.

1.9. 1.9, 1.9, 1.9, 2.2, 2.3, 2.4, 2.4, 2.4, 2.4

A. 1.9

B. 2.1

C. 2.25

D. 2.4

Answer Key

2. A number of cases of malaria are collected over 10 years with extreme variation in data. The best measure to calculate average is:

A. Arithametic mean

B. Mode

89

C. Geometric mean

D. Median

Answer Key

3. In a population study for malaria over the past few years, the number of case reported were 20, 5000, 100, 80, 60, 70, 40, 60, 80. The average is best represented by:

A. Arithemetic mena

B. Mode

C. Geometric mean

D. Median

Answer Key

4. Malaria incidence in a village in the year 2000 is 430, 500, 410, 160, 270, 210, 300, 350, 4000, 430, 480, 450. Which of the following is the best indicator for assessment of malaria incidence in that village by the epidemiologist?

A. Arithemetic mean

B. Gemetric mean

C. Median

D. Mode

Answer Key

5. Ten babies are born in a hospital on same day. All weight 208 kg each. Calculate the standard deviation.

A. Zero

B. One

C. Minus one

D. 0.28

Answer Key

6. Blood pressure samples from two community are

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best campared by:

A. Paired t-test

B. Student's t-test

C. Chi-square test

D. Cohort study

Answer Key

7. In statistics, spread of dispersion is described by:

A. Median

B. Mode

C. Standard deviation

D. Mean

Answer Key

8. Calculate the mode of 70, 71, 72, 70, 70.

A. 70

B. 71

C. 71.5

D. 72

Answer Key

9. In an epidemiological study, the incubation periods obtained were 2, 5, 8, 10, 25, 10, and 30. The median is calculated to be:

A. 50

B. 22.5

C. 10

D. 5

Answer Key

10. Among the measure of dispersion which is the most frequently used:

A. Range

B. Mean

C. Median

91

D. Standard deviation

Answer KeyAnswer Key

1. C 2. B 3. B 4. C 5. A

6. A 7. C 8. A 9. C 10. D

1. What is the mode in statistics?

A. Value of middle observation

B. Arithmetic mean

C. Most commonly occurring value

D. Difference between the highest and lowest value

Answer Key

2. Square root of deviation is called:

A. Standard deviation

B. Standard error

C. Mean deviation

D. Range

Answer Key

3. In normal distribution curve, sampling values following:

A. Mean=Median

B. Mean=S.D

C. Mean=Variant

D. Mean= 2 x median

Answer Key

4. Which is false about normal distribution curve?

A. In a normal curve 95% of values in within 1 SD

92

B. Mean, mode and median coincidence

C. Median is mid value

D. Mode is commonest occurring value

Answer Key

5. Shape of a normal curve is:

A. Symmetrical

B. Curvilinear

C. Linear

D. Parabolic

Answer Key

6. The area under normal distribution curve for S.D. of 2 is:

A. 68%

B. 95%

C. 97.5%

D. 100%

Answer Key

7. In a standard normal curve the area between one standard deviation on either side will be:

A. 68%

B. 85%

C. 97.5%

D. 99%

Answer Key

8. Normal distribution curve is explained using:

A. Mean and sample

B. Mean and median

C. Median and standard deviation

D. Mean and standard

93

deviation

Answer Key

9. In a highly skewed distribution central tendency is better explained by:

A. Mode

B. Median

C. Standard deviation

D. Mean

Answer Key

10. Which is false about normal distribution curve?

A. 95% of values fall within 1 S.D.

B. Mean, median and mode coincide

C. Median is the midvalue

D. Mode is commonest occurring value

Answer Key

11. Right sided skewed distribution causes:

A. Median is more than mean

B. S.D. is more than variance

C. "Tail" to the left

D. "Tail" to the right

Answer Key

12. In a normal distribution curve, the true statement is:

A. Mean = SD

B. Median = SD

C. Mean = 2 Median

D. Mean = Mode

94

Answer Key

13. If the mean is 230 and the standard error is 10, the 95% confidence limits will be:

A. 210 to 250

B. 220 to 240

C. 225 to 235

D. 230 + or -210

Answer Key

14. Among the following which is most significant P value?

A. 0.005

B. 0.05

C. 0.01

D. 0.1

Answer Key

15. The number of degrees of freedom in a table of (4x4):

A. 4

B. 8

C. 9

D. 16

Answer KeyAnswer Key

1. C 2. A 3. A 4. A 5. A

6. B 7. A 8. D 9. A 10. A

11. C 12. D 13. A 14. A 15. C

1. "Confidence limits" are:

A. Mean +/- Standard error

B. Median + Standard

95

error

C. Mean + Range

D. Mean standard deviations

Answer Key

2. Sum of all squares of deviation from the mean is called:

A. Mean

B. Mode

C. Variance

D. Standard Error

Answer Key

3. Limits of confidence of a hypothesis is determined by:

A. Power factor

B. Level of significance

C. 1-power factor

D. 1-level of significance

Answer Key

4. Which is true about cluster sampling?

A. Every month case is chosen fro study

B. A natural group is taken as sampling unit

C. Stratification of population

D. Involves use of random numbers

Answer Key

5. In a community of 3000 people, 80% are Hindus, 10% Muslims, 5% Sicks, 4% Christians, and 1% Jains. To select a sample of 300 people to analyze food habits, ideal sampling method would be:

96

A. Simple random sampling

B. Stratified random sampling

C. Systematic random sampling

D. Inverse sampling

Answer Key

6. Mean of 25 variables is 2, Standard deviation is 2, Standard error of mean is:

A. 0.4

B. 0.2

C. 2.0

D. 10

Answer Key

7. Cholesterol value are obtained in a group of people before and after giving drug A. the appropriate statistical test used to analyze the data is:

A. Paired t-test

B. Unpaired t-test

C. Fischer's test

D. Chi-square test

Answer Key

8. Calculate standard error for population of size of 25 persons suffering from fever of history of 8 days and with standard deviation of 2.

A. 0.4

B. 0.2

C.0.%

D. 1.6

Answer Key

9. In a population of 100

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females the mean hemoglobin concentration was 10 and standard deviation was 1. The standard error is:

A. 0. 01

B. 0.1

C 0.5

D. 1.6

Answer Key

10. An investigator was to study the association between maternal intake of iron supplements (yes or no) and birth weights (in grams) of newborn babies. He collects relevant data from 100 pregnant women and their newborns. What is the appropriate statistical investigation in this context?

A. Chi-square test

B. Unpaired or independent t-test

C. Analysis of variance

D. Paired t-test

Answer KeyAnswer Key

1. A 2. C 3. B 4. D 5. B

6. A 7. A 8. A 9. B 10. B

1. In a drug trial, one group showed 40% response and the group with the test drug showed 60% response. The two results can be statistically compared for significance by:

A. Chi-square test

B. Paired test

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C. t-test with different measures

D. Fischer test

Answer Key

2. In a group of 100m children, the weight of child is 15 kg. The standard error is 1.5 kg. Which of the following is true?

A. 95% of all children weight between 12 and 18 kg

B. 95% of all children weight between 13.5 and 16.5 kg

C. 99% of all children weight between 12 and 18 kg

D. 99% of all children weight between 12 and 18 kg

Answer Key

3. The following statistics is used to measure the linear association between two characteristics in the same individuals:

A. Coefficient of variation

B. Coefficient of correlation

C. Chi-square

D. Standard error

Answer Key

4. Which of the following test of significance can be used to compare unrelated variables when values are all binary?

A. t-test

B. Chi-square test

C. Proportion test

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D. Correlation test

E. Regression test

Answer Key

5. What is true about Chi-square test?

A. Expected and observed values are always equal

B. Mutually exclusive

C. Mutually non-exclusive

D. Indicates median

Answer Key

6. In Chi-square test degree of freedom 1, Chi-squire value= 6.7, then P-value will be:

A. > 0.5

B. <. 0.1

C. < 1 .0

D. < 0. 05

Answer Key

7. Regarding paired t-test true is:

A. Hypertension in a person before and after treatment can be studied

B. Continuous variables in a single sample

C. Different variables in a single sample

D. Unrelated samples can be compared

8. Complete correlation between height and weight is best given by:

A. -1

B. +1

C. 0

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D. Infinity

9. Which of the following is a pre-requisite for the Chi-square test compare?

A. Measures should be in continuous scale

B. Both samples need not be mutually exclusive

C. Both samples should be mutually exclusive

D.. Samples should follow normal distribution

10. The Chi-square test is used to measure the degree of:

A. Causal relationship between exposure and effect

B. Correlation between two variables

C. Association between two variables

D. Agreement between two observations

Answer Key

1. A 2. A 3. B 4. A 5. B

6. D 7. A 8. B 9. C 10. B

2.

1. In a drug trial, one group showed 40% response and the group with the test drug showed 60% response. The two results can be statistically compared for significance by:

A. Chi-square test

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B. Paired test

C. t-test with different measures

D. Fischer test

Answer Key

2. In a group of 100m children, the weight of child is 15 kg. The standard error is 1.5 kg. Which of the following is true?

A. 95% of all children weight between 12 and 18 kg

B. 95% of all children weight between 13.5 and 16.5 kg

C. 99% of all children weight between 12 and 18 kg

D. 99% of all children weight between 12 and 18 kg

Answer Key

3. The following statistics is used to measure the linear association between two characteristics in the same individuals:

A. Coefficient of variation

B. Coefficient of correlation

C. Chi-square

D. Standard error

Answer Key

4. Which of the following test of significance can be used to compare unrelated variables when values are all binary?

A. t-test

B. Chi-square test

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C. Proportion test

D. Correlation test

E. Regression test

Answer Key

5. What is true about Chi-square test?

A. Expected and observed values are always equal

B. Mutually exclusive

C. Mutually non-exclusive

D. Indicates median

Answer Key

6. In Chi-square test degree of freedom 1, Chi-squire value= 6.7, then P-value will be:

A. > 0.5

B. <. 0.1

C. < 1 .0

D. < 0. 05

Answer Key

7. Regarding paired t-test true is:

A. Hypertension in a person before and after treatment can be studied

B. Continuous variables in a single sample

C. Different variables in a single sample

D. Unrelated samples can be compared

8. Complete correlation between height and weight is best given by:

A. -1

B. +1

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C. 0

D. Infinity

9. Which of the following is a pre-requisite for the Chi-square test compare?

A. Measures should be in continuous scale

B. Both samples need not be mutually exclusive

C. Both samples should be mutually exclusive

D.. Samples should follow normal distribution

10. The Chi-square test is used to measure the degree of:

A. Causal relationship between exposure and effect

B. Correlation between two variables

C. Association between two variables

D. Agreement between two observations

Answer Key

1. A 2. A 3. B 4. A 5. B

6. D 7. A 8. B 9. C 10. B

2.

1. Prevalence is:

A. Rate

B. Ratio

C Proportion

D. Mode

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2. To compare two population, the best index is:

A. Standardized death rate

B. Infant mortality rate

C. Crude birth rate

D. Couple protection rate

3. All are morbidity indicators, except:

A. Period of stay in hospital

B. Doctor population ratio

C. Attendance at outpatient department

D. Notification rates

Answer Key

4. Incidence is defined as:

A. Number of cases existing in a given population at a given moment

B. Number of cases existing in a given period

C. Number of new cases occurring during a specific period

D. Number of old cases present

5. Relative risk can be obtained from:

A. Case study

B. Cohort study

C. Case control study

D. Experimental study

Answer Key

6. In a village of 1 lakh

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population, among 20,000 exposed to smocking, 200 developed cancer, and among 40,000 people unexposed , 40 developed cancer. The relative risk of smocking in the development of cancer is:

A. 20

B. 10

C. 5

D. 15

Answer Key

7. Calculate the Odd's ratio. (ad/bc)

Diseased

Positive 30

Negative 20

A. 0.44

B. 1.5

C. 0.8

D. 2.25

Answer Key

8. Death rate of two countries is compared by:

A. Crude death rate

B. Proportional crude rate

C. Standardized mortality rate

D Age specific death

Answer Key

9. Case control study is used for:

A. Finding rare cause

B. Finding multiple risk factors

C. Finding incidence rate

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D. Finding morbidity rates

Answer Key

10. When launching a study many respondent are invited, some of whom fail to come. This is called:

A. Response bias

B. Volunteer bias

C. Selection bias

D. Berkesonian bias

Answer Key

11. Most important characteristic of case control study is:

A. Odd's ratio estimation

B. Problem bias

C .Yields incidence rate

D. Expensive

Answer Key

12. All are true about cohort studies, except:

A. Prospective

B. Useful for rare diseases

C. Necessary for incidence

D. Expensive

Answer Key

13. Which is the most appropriate method of research for studying incidence of diarrhea in a community?

A. Cross-sectional study

B. Cohort study

C. Case control study

D. Double-blind placebo study

Answer Key

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14. Best method to calculate the incidence rate is:

A. Case control study

B. Sentinel surveillance

C. Cohort study

D. Cross-sectional prevalence study

Answer Key

15. Relative risk could show an association between:

A. Smocking ad cancer

B. OCP and pregnancy

C. Efficacy of 2 drugs

D. Altitude and endemic goiter

Answer KeyAnswer Key

1. B 2. A 3. B 4. C 5. B

6. B 7. D 8. C 9. B 10. B

11. A 12. B 13. B 14. C 15. A

1. The ratio between the incidence of disease among exposed and non-exposed is called:

A. Causal risk

B. Attributable risk

C. Relative risk

D. Odd's ratio

Answer Key

2. Which is false about cohort study?

A. Incidence can be measured

B. Used to study chronic

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diseases

C. Expensive

D. Always prospective

Answer Key

3. Prevalence of disease in a community can be found out by:

A. Case control study

B. Cohort study

C. Cross-sectional study

D. Experimental study

Answer Key

4. True about case control study are all, except:

A. Quick results

B. Incidence rate measure

C. Proceeds from effect to cause

D. Relatively inexpensive

Answer Key

5. Study of lung cancer in non-smokers is:

A. Unifactorial

B. Multifactorial

C. Passive smocking also increases risk of cancer

D. Beedi smokers carry higher risk than cigarette smokers

Answer Key

6. Temporal association between a risk factor and the disease relates to:

A. Does-response relationship

B. Duration - response relationship

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C. One to-one relationship

D. Cause and effect relationship

Answer Key

7. Percentages in the segments are indicated by:

A. Bar charts

B. Histogram

C. Pictogram

D. Pie charts

Answer Key

8. In a community with prevalence of HIV 5%, if the sensitivity is 95% and specificity is 95% of ELISA, what is the predictive value of the test?

A. 100%

B. 50%

C. 25%

D. 0%

Answer Key

9. Parameters of sensitivity and specificity are used for assessing:

A. Criterion validity

B. Construct validity

C. Discriminant validity

D. Content validity

Answer Key

10. Secondary attack rate reflects:

A. Severity

B. Communicability

C. Fatality

D. Infectivity

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Answer KeyAnswer Key

1. C 2. D 3. A 4. B 5. B

6. D 7. D 8. B 9. A 10. B

 

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