types of research designs rs mehta
TRANSCRIPT
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TYPES OF RESEARCH &
RESEARCH DESIGNS
1Dr. R S Mehta, MSND, BPKIHS
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Types of Study Design: • There is no best type of study design
• The context, assumptions, paradigms and perspectives decide the type of research methodology
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How to Choose a Research Design
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• Does it adequately test the hypothesis?• Does it identify & control extraneous factors?• Are results generalizable?• Can the hypothesis be rejected or retained
via statistical means?• Is the design efficient in using available
resources?
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Selecting a Research Design
1. Level of knowledge2. Nature of the research phenomenon3. Nature of the research purpose4. Ethical considerations5. Feasibility6. Validity and availability of data7. Precision8. Cost
4Dr. R S Mehta, MSND, BPKIHS
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1. Define the problem ( Characteristics) 2. Specify the objectives (Hypothesis) 3. Select design or type of study 4. Select study population 5. Collect data 6. Analyze data 7. Determine conclusions
Anatomy of Research
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Dr. R S Mehta, MSND, BPKIHS 6
Select design or type of study
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Types of ResearchFrom the view point of
ApplicationPure
Research
Applied Research
ObjectivesExploratory Research
Descriptive Research
Correlation Research
Explanatory Research
Type of Information
SoughtQuantitative Research
Qualitative Research
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TYPE OF STUDIES Observational
1. Correlational study
2. Case reports and case series
3. Cross sectional survey
4. Case-control study
5. Cohort study Experimental
1. Community trials
2. Clinical trials – individuals Dr. R S Mehta, MSND, BPKIHS
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Study Designs
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1. Descriptive Studies2. Cross-Sectional Studies3. Cohort Study4. Case Control5. Randomized Controlled Trials6. Survey Research
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Critical Thinking Decision Path: Non-experimental Design Choice
10Dr. R S Mehta, MSND, BPKIHS
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Health Sciences and Nursing ResearchNon-interventional Interventional
Explorative
Descriptive Analytical
Pre-experimental
Quasi-experimenta
l
True-Experiment
- Case study- Cross-
sectional- Longitudinal- Etc.
- Cross-sectional
- Case control
- Cohort - Etc
- CRD- RBD- FD- etc
11Note: CRD-complete random design, RBD-random block design, FD- factorial
designDr. R S Mehta, MSND, BPKIHS
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4 Types of Research• Basic research• Applied research• Action research• Evaluation research
12Dr. R S Mehta, MSND, BPKIHS
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Basic Research• Also known as fundamental research
(sometimes pure research) is research carried out to increase understanding of fundamental principles.
• Many times the end results have no direct or immediate commercial benefits
• Basic research can be thought of as arising out of curiosity.
• However, in the long term it is the basis for many commercial products and applied research.
• Basic research is mainly carried out by universities 13Dr. R S Mehta, MSND, BPKIHS
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Applied Research• Concern with addressing problem of the world
as they are perceived by participants, organization or group of people
• Action oriented and aims to assess, describe, document or inform people concerned about the phenomenon under investigation
• Findings are intended to have immediate and practical value
• In the field of education, policy, evaluation and contract are all examples of applied research
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Action ResearchAction Research is simply a form of self-reflective enquiry undertaken by participants in social situations in order to improve the rationality and justice of their own practices, their understanding of these practices, and the situations in which these practices are carried out.
Wilf Carr and Stephen Kemmis (1986)
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Evaluation research• Major concern is practical application• Tends to be viewed as an isolated case study
though the methodologies may be transferable• Rooted in values and politics• Is immediately prescriptive based upon logic and
experience• Reports are written for implementers, users and
other interested people• The extent of dissemination is controlled by
sponsor16Dr. R S Mehta, MSND, BPKIHS
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RESEARCH DESIGNSQUANTITATIVE QUALITATIVE
• Experimental study• Quasi-experimental• Survey study• Correlational study
• Ethnography• Case study• Historical study
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Types of Study Design: Details
Dr. R S Mehta, MSND, BPKIHS 18
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1. Descriptive Studies:
Person, Place and Time
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Descriptive Epidemiology
• Includes activities related to characterizing the distribution of diseases within a population
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• Concerns activities related to identifying possible causes for the occurrence of diseases
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Descriptive Epidemiology
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PERSON
PLACE
TIME
Think of this as the standard dimensions used to track the occurrence of a disease.
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Descriptive Research Design:–Describe facts–Discover new facts–Not invent new theory and methods–Largest effort given on data
collection– It answers questions: satisfy
curiosity–Solve problems
22Dr. R S Mehta, MSND, BPKIHS
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2. Cross-Sectional Studies
23Dr. R S Mehta, MSND, BPKIHS
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Features of C-S Studies
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• Snapshot in time–e.g. - cholesterol measurement and
ECG measured at same time• Determines prevalence at a point in
time• Therefore, C-S is a prevalence study
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Advantages of C-S Studies
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• Short term• Fewer resources required• Less statistical analysis• More easily controlled• Design less complex
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Advantages of C-S Studies (Cont.)
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• Provide relationship between attributes of disease and characteristics of various groups, e.g. elderly group
• Data is useful for planning of health services and medical programs
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Disadvantages of C-S Studies
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• Represent only those who are surveyed• Identify prevalence, not incidence
necessarily–excludes cases that died before study
was done• Show association with survival - not risk of
development
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Disadvantages of C-S Studies (cont.)
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• People who are ill may not show up for survey -*Healthy Person Effect
• Often, not possible to establish temporal relationship between exposure and onset–e.g. does high cholesterol precede CHD?
• Not too effective if disease levels are low, as difficult to establish a causal relationship
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Design of a C-S Study
29Dr. R S Mehta, MSND, BPKIHS
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Design of a C-S study (Cont.)
30Dr. R S Mehta, MSND, BPKIHS
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Cross-Sectional Study
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inelig ible
phys ically active&
C H D
phys ically ac tive&
no C H D
phys ically inac tive&
C H D
phys ically inactive&
no C H D
partic ipation no partic ipation
eligible
F arm ers
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Cross-Sectional Study
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Disease
Exposure yes no total
yes a b a + b
no c d c + d
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3. Cohort Study
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Group by common characteristicsStart with a group of subjects who lack a positive history of the outcome of interest yet are at risk for it (cohort). Think of going from cause to effect.
The exposure of interest is determined for each member of the cohort and the group is followed to document incidence in the exposed and non-exposed members.
Cohort Studies
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When is a cohort study warranted?
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• When good evidence suggests an association of a disease with a certain exposure or exposures.
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Changes and variation in the disease or health status of a study population as the study group moves through time.
“Generation effect”
Cohort Effect
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• Prospective (concurrent)
• Retrospective (historical)
• Restricted (restricted exposures)
Types of Cohort Studies
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Types of Cohort Studies
Prospective – cohort characterized by determination of exposure levels (exposed vs. not exposed) at baseline (present) and followed for occurrence of disease in future
Groups move through time as they age Retrospective - makes use of historical data to determine exposure level at some baseline in the past and then determine subsequent disease status in the present.Restricted - limited exposure, narrow behavior (e.g. military)
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Prospective Studies
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• Also called– longitudinal– concurrent– incidence studies
• Looking into the future• Example:
Study of coronary heart disease (CHD)
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The essential characteristic in the design of cohort studies is the comparison of outcome in an exposed group and a nonexposed group (or a group with a certain characteristic and a group w/o that characteristic). A study population can be chosen by selecting
groups for inclusion in the study on the basis of whether or not they were exposed
Design of a Cohort Experiment
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There are two basic ways to generate cohort groups.
Select a cohort (defined population) BEFORE any of its members become exposed or before the exposures are identified.
Select a cohort on the basis of some factor (e.g., where they live) and take histories (e.g., blood tests) on the entire population to separate into exposed and non-exposed groups.
Regardless of which selection approach is used, we are comparing exposed and non-exposed persons.
Selection of Cohort Groups
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Design of a Cohort Experiment
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Design of a Prospective Cohort Experiment
Major problem with a prospective cohort design is that the cohort must be followed up for a long period of time.
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Data Gathering
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• Person - to - person• Drop off questionnaire• Mailed to people• Telephone interview• Newsletter or magazine
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Potential Biases in Cohort Studies
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• Information bias• Bias in estimation of the outcome• Bias from non-response • Bias from losses to follow-up• Analytic bias
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Advantages of Prospective Cohort Studies
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• Large sample sizes• Certain diseases or risk factors targeted• Can be used to prove cause-effect• Assess magnitude of risk• Baseline of rates• Number and proportion of cases that can be
prevented
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Advantages of Prospective Studies (cont’d)
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• Completeness and accuracy• Opportunity to avoid condition being
studied• Quality of data is high• Considers seasonal and other variations
over a long period• Tracks effects of aging process
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Disadvantages of Prospective Cohort Studies
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• Large study populations required– not easy to find subjects
• Expensive• Unpredictable variables• Results not extrapolated to general population• Study results are limited• Time consuming/results are delayed• Requires rigid design and conditions
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Disadvantages of Prospective Studies (cont’d)
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• Subjects lost over time (dropouts)• Costs are high• Logistically demanding• Maintaining quality, validity, accuracy
and reliability can be a problem
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Cohort/ Longitudinal Studies
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Design
Sample Of Population
High Exposure
Medium Exposure
Low Exposure
No Exposure
Outcome
Outcome
Outcome
OutcomeDr. R S Mehta, MSND, BPKIHS
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Prospective Cohort Design
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Retrospective Cohort Design
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COHORT STUDY
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Source Population Cases(= Exposed, =Unexposed) (□= Exposed, ■=Unexposed)
■ □ □ ■ ■ ■ □ ■ □ ■ □ □ ■ □ ■ □
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4. Case Control Study
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CASE-CONTROL STUDIESSOME KEY POINTS
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• Frequently used study design• Participants selected on the basis of whether or
not they are DISEASED (remember in a cohort study participants are selected based on exposure status)
• Those who are diseased are called CASES.• Those who are not diseased are called
CONTROLS.
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Case-Control Study
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inelig ible
exposed un exposed
bad ou tcom e(cases)
exposed unexposed
good ou tcom e(con trols)
partic ipation no partic ipation
eligib le
S ou rce P opu lation
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Case-Control Design
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Case-Control Design
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Subjects With Outcome of Interest
Design
Appropriate Control Group Without Outcome Of Interest
Measure factors
Compare factors
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Case-Control Studies
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dcNo
baYes
Present
Outcome
Absent
Exposure to intervention or causal factor
Direction
Of
Sampling
Results
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Case- Control Design: Advantages
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1. Valuable for studying rare conditions.2. Short duration3. Relatively inexpensive4. Relatively smaller sample needed5. Yields odd ratio (usually a good
approximation of relative risk)
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Case- Control Studies: Disadvantages
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1. Limited to one outcome variable2. Potential bias from selection of cases and
controls3. Does not establish sequence of events4. Potential bias in measuring exposure5. Potential survivor bias6. Does not yield absolute risk estimates.
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PAST PRESENT
Exposure recall Cases & ControlsSelected
Example: lung cancer cases and non-cancerous controls recall past exposure to cigarette smoke
Because participants are selected on the basis of disease, exposures for ALL PARTICIPANTS are obtained RETROSPECTIVELY…………..
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SELECTION OF CASES
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• Decide on a specific case definition based on a medically diagnosed condition.When diagnosis relies on subjective assessment case definition
will be less precise.• Must consider what criteria will confirm the case definition:
Lung cancer confirmed by biopsyOsteoporosis confirmed by bone density measurementsStudying mild forms of a disease results in largest possible case
group but may include non-cases (misclassification)Studying severe forms of a disease decrease the probability of
misclassification
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SELECTION OF CONTROLS
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• Controls should be representative of the referent population from which cases are selected (i.e. comparable)–Controls should have the potential to become
cases; Controls should also be candidates for having the disease of interest
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SELECTION OF CONTROLS (2)
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• Different Types of Controls………
–Population controls• Randomly selected individuals from the
population like RDD (random digit dialing)
–Neighborhood controls• Individuals that live in the same
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SELECTION OF CONTROLS (3)
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–Friends controls• best friends of cases• spouses or siblings of cases
–Hospital controls• Individuals at the same hospital with
cases
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SELECTION OF CONTROLS (4)
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• The investigator can elect to use more than one TYPE of control for each case……. When there is no ONE group similar enough to cases.
EXAMPLE: A particular leukemia case may have both a neighborhood control (similar to case in terms of environment) and a sibling control (similar to case in terms of genetic background).
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Cases & Controls
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• For each CASE in the study, a control is selected• How many controls should be selected per case?
–1:1 is usual– Increasing the ratio of controls to cases increases
the precision and efficiency of the analysis– It also increases the cost to undertake the study
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MATCHING
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• CHARACTERISTICS OFTEN USED
–age–gender–body mass index (weight / height2)–smoking status–marital status
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MATCHING (2)
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• GROUP MATCHING• Based on proportions• Idea is to select a control group with a certain
characteristic identical to cases in the same proportion as it appeared in cases.
Example: If 25% of cases in your study smoke you would select a control population that included 25% smokers.
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GROUP MATCHING EXAMPLE
CASE POPULATION CONTROL POPULATION
Smokers
Non-Smokers
Smokers
Non-Smokers
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MATCHING (3)
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2) INDIVIDUAL MATCHING (matched pairs)• For every individual case a control is selected who
is identical to the case on certain characteristics.
Example: If your first case is a 25 year-old women who smokes then you would find a control who is 25, female and a smoker. So you are matching on age, gender, and smoking status.
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MATCHED PAIRS EXAMPLE
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CASE
CONTROL
CASE
CONTROL
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POTENTIAL PROBLEMS WITH MATCHING
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• It will be difficult to find controls if too many variables are selected for matching.
• Variables used for matching can not be studied as exposures or confounders.
• OVERMATCHING – when variables related to disease are inadvertently matched upon.
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Classic 2 x 2 Table for a Case-Control Study if in the POPULATION
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Disease No Disease
Exposure A B
No Exposure C D
Odds Ratio = A/C = AD B/D BC
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Example: Hypothetical data
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Cases Controls
Exposed 141 133Unexposed 1250 4867
Total 1391 5000
ODDS RATIO = 141 * 4867 = 4.13 133 * 1250Dr. R S Mehta, MSND, BPKIHS
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Interpretation of the Odds Ratio…
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If:OR = 1 then exposure is NOT related to
disease
OR>1 then exposure is POSITIVELY related to
disease
OR<1 then exposure NEGATIVELY related to disease
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Interpretation:
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The odds that those with the outcome had the exposure is 4.13 times greater than those who do not have the outcome
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Strengths:
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1. Quick and inexpensive2. Well-suited to the evaluation of outcomes
with long latent periods3. Optimal for the evaluation of rare diseases4. Can examine multiple etiologic factors for a
single disease
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Limitations:
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1. Cannot directly compute incidence rates of disease
2. Temporal relationship between exposure and disease may be difficult to establish
3. Prone to bias4. Insufficient to evaluate rate exposure
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TYPES OF RESEARCH &
RESEARCH DESIGNS
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Types of Study Design: • There is no best type of study design
• The context, assumptions, paradigms and perspectives decide the type of research methodology
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Health Sciences and Nursing ResearchNon-interventional Interventional
Explorative
Descriptive Analytical
Pre-experimental
Quasi-experimenta
l
True-Experiment
- Case study- Cross-
sectional- Longitudinal- Etc.
- Cross-sectional
- Case control
- Cohort - Etc
- CRD- RBD- FD- etc
83Note: CRD-complete random design, RBD-random block design, FD- factorial
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5. Randomized Controlled Trials
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Randomized Controlled Trials
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• Similar groups of individuals from same source population are allocated at random to receive or not to receive an intervention, then observed for occurrence of outcome(s).
DESIGN
Subjects with condition of Interest
Experimental Group
Control
Outcome
Outcome
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A Factorial RCT for Two Studies for the Price of One
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RCT– the “gold standard” of research designs.
They thus provide the most convincing evidence of relationship between exposure and effect. Example: • trials of hormone replacement
therapy in menopausal women
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Randomized Controlled Trial : Advantages
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1. Comparability due to randomization and same effect of known and unknown confounders gets eliminated
2. Experiments provide strong evidence of cause and effect.
3. Allows standardization of eligibility criteria, maneuver and outcome assessment.
4. Allows use of statistical methods with few inbuilt assumptions.
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Randomized Controlled Trial : Disadvantages
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1. May be expensive in terms of time, money and people.
2. Many research questions are not suitable due to ethics, likely co-operation or rarity of outcome.
3. To a greater or lesser extent RCT tends to be an artificial situation.
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Suitable Study Design
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Issues Study Design
Diagnosis Cross sectional Therapy RCT (Non-RCT)Prognosis Prospective cohortCause Cohort
Case controlDescription Case Series
Cross Sectional
However, more than one study design can be used to answer any given question of causal association
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6. Survey Research
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Survey research• Survey research is often used to assess
thoughts, opinions, and feelings• Psychologists and sociologists often use survey
research to analyze behavior, while it is also used to meet the more pragmatic needs of the media, such as, in evaluating political candidates, public health officials, professional organizations, and advertising and marketing directors.
• A survey consists of a predetermined set of questions that is given to a sample.
• Every day you find in TV and Radio?Dr. R S Mehta, MSND, BPKIHS 92
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Survey design: • Evaluative• Comparative• Short-term• Long-term• Longitudinal• Cross-sectional• Cross-cultural
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Questions to Ask Before Doing Survey Research
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• Do you have a clear hypothesis?• Do your questions focus on that
hypothesis?• Will participants answers provide
accurate answers to your questions?• To whom will your results apply?
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Planning a Survey
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• Deciding on a research question• Choosing the format of your questions• Choosing the format of your interview--if
you use an interview• Editing your questions• Sequencing your questions• Refining your survey instrument• Choosing a sampling strategy
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Editing Questions: Nine Mistakes to Avoid
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1. Avoid leading questions
2. Avoid questions that invite the social desirability bias
3. Avoid double-barreled questions
4. Avoid long questions
5. Avoid negations6. Avoid irrelevant
questions7. Avoid poorly
worded response options
8. Avoid big words9. Avoid ambiguous
words & phrases
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Survey researchers should carefully construct the order of questions in a questionnaire
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7. Case Study• Explores in depth a program, event, activity, process,
or one or more individuals• Bounded (separated out for research) by time, place
and activity• Researcher collects detailed information using a
variety of data collection procedures over a sustained period of time (Stake & Creswell)
• A method of learning about a complex instance based on a comprehensive understanding of that instance obtained by extensive description and analysis of that instance taken as a whole
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Case Study/Reports• Detailed presentation of a single case or
handful of cases• Generally report a new or unique finding
• e.g. previous undescribed disease• e.g. unexpected link between diseases• e.g. unexpected new therapeutic effect• e.g. adverse events
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Case Series• Experience of a group of patients with a
similar diagnosis• Assesses prevalent disease• Cases may be identified from a single or
multiple sources• Generally report on new/unique
condition• May be only realistic design for rare
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Case Series• Advantages
• Useful for hypothesis generation• Informative for very rare disease with few
established risk factors• Characterizes averages for disorder
• Disadvantages• Cannot study cause and effect relationships• Cannot assess disease frequency
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8. Historical Study• Focuses primarily on the past• Persuing documents of the period• Examining relics (left over)• Interviewing individuals who lived during that time• Reconstruct what happened during that time as
completely as possible• Systematic collection and evaluation of data to
describe, explain, and thereby understand actions or events that occurred in the past
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104
9. Experimental Research Designs
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Aim: • The aim of experimental research is to
investigate the possible cause and effect relationship by manipulating one independent variable to influence the other variable in the experimental group and by controlling the other relevant variables and measuring the effects of the manipulation by some statistical means.
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106
Experimental Research Triesto Establish Cause and Effect
• Selection of a good theoretical framework• Application of appropriate experimental design• Use of correct statistical model and analysis• Proper selection and control of independent
variables• Appropriate selection and measurement of
dependent variables• Correct interpretation of results
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Characteristics or Features of Experimental Design
1. Manipulation2. Control3. Randomization
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Experimental Design• Advantages
– Best establishes cause-and-effect relationships
• Disadvantages– Artificiality of experiments– Feasibility– Unethical
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Types of Experimental Designs
• True-Experimental (Simple)• Quasi-Experimental• Pre-Experimental
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True, Qusi, & Pre- Experimental Study
Randomization, Control and Manipulation
• True exp.: All 3: R C M• Quasi exp.: M + R or C • Pre exp.: M, no R & no C
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Steps in Experimental Research• State the research problem• Determine if experimental methods apply• Specify the independent variable(s)• Specify the dependent variable(s)• State the tentative hypotheses• Determine measures to be used• Pause to consider potential success• Identify intervening (extraneous) variables• Formal statement of research hypotheses• Design the experiment• Final estimate of potential success• Conduct the study as planned• Analyze the collected data• Prepare a research report
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10. Ex Post Facto Study• Variable of interest is not subject to direct
manipulation but must be chosen after the fact.E.g., Define two groups of people according to a certain characteristic (e.g., history of trauma) and measure how they respond in terms of anxiety to a certain stimulus (e.g., watching violent film).
• Limitation – self-selection bias, cohort effects.
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11. Meta Analysis
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• Combining the results from many studies dealing with the same topic.
• Statistically combines results of existing research to estimate overall size of relation between variables
• Helps in • Developing theory • Identifying research needs, • Establishing validity
• Can replace large-scale research studies• Better than literature reviews
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• It is similar to a simple cross-sectional study, in which the subjects are individual studies rather than individual people.
• A review of literature is a meta-analytic review only if it includes quantitative estimation of the magnitude of the effect and its uncertainty (confidence limits).
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Meta analysis
Quantitative approach for
systematically combining results of previous research to arrive at conclusions about the body of research.
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• Quantitative : numbers• Systematic : methodical• combining: putting together• previous research: what's already done• conclusions: new knowledge
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Steps for Conducting A Meta-Analysis
A. Data SourcesB. Study SelectionC. Data AbstractionD. Statistical Analysis
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Statistical conceptsThe impact of fish oil consumption on Cardio-vascular diseases
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Forest plot
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Advantages of Meta-Analysis
1. Study question specific & narrow2. Data collection comprehensive &
specific3. Study selection based on uniformly
applied criteria4. Data synthesis quantitative
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12. Qualitative Research
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Choice of Colours
• 1. What colour would you like the most?
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2.What do you associate this colour with?Good luckloveConfidenceTruthfulnessLivelyDanger…
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3. What is the source of this knowledge?–Own Idea–Own Belief–Own observation–Own experiences –Cultural and Traditional–Books & articles– etc
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• Not every thing can be quantified.• Some valuable ideas, opinions,
perceptions, experiences, behaviours, qualities can be described only in words
• These subjective things are shared between people, but the meanings may be distorted in the process of communication and recording.
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• Although subjective, these aspects often add richness and depth
• The art of the doctor and the experience of being human are aspects that need a qualitative approach to investigate/research properly.
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• Qualitative Research - investigation in which the researcher attempts to understand some larger reality by examining it in a holistic way or by examining components of that reality within their contextual setting.
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Qualitative Research• ‘Qualitative Research…involves finding out what
people think, and how they feel - or at any rate, what they say they think and how they say they feel. This kind of information is subjective. It involves feelings and impressions, rather than numbers’
- Bellenger, Bernhardt and Goldstucker, Qualitative Research in Marketing, American Marketing Association
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Universal
Specific
Explanatory
Descriptive Subjective
Objective
Universal ------------------------------ SpecificObjective ------------------------------ SubjectiveExplanatory ---------------------------- Descriptive
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Characteristics of Qualitative Research
• Purpose is understanding• Oriented toward discovery• Uses subjective data• Extracts meaning from data• Interprets results in context• Focus is holistic
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Organizational Structures (Types)
Historical Analysis Ethnography Phenomenology Life History,
Chronology,Historiography
Case Study
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Ethnographic Design• Examining a group of individuals in the setting where
they live and work, and in developing a portrait of how they interact
• Describing, analyzing and interpreting a group’s shared patterns of behavior, beliefs and language that develop over time
• Provides a detailed picture of the group, drawing on various sources of information
• Describes the group within its settings, explores themes or issues that develop over time as the group interacts
• Data analysis emphasize on description and explanation rather than quantification and statistical analysis (Atkinson & Hammersley, 1994)
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Phenomenology• Definition: “Phenomenology is an
approach which attempts to understand the hidden meanings and the essence of an experience together with how participants make sense of these.” (Grbich 2007, p. 84).
• Strengths: Phenomenology is used to explore, describe, document rich details of people’s experiences, especially changes in feelings and experiences over time.
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phenomenology
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Qualitative Data Collection Techniques
• In depth Interviewing • Focus Groups • Participant Observations• Ethnographic Studies• Projective Techniques
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Analysis Qualitative Data: An Approach
• Categorisation• Unitising data• Recognising relationships and developing
the categories you are using to facilitate this
• Developing and testing hypotheses to reach conclusion
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Tools for helping the Analytical Process
Summaries• Should contain the key points that emerge from
undertaking the specific activitySelf Memos• Allow you to make a record of the ideas which
occur to you about any aspect of your research, as you think of them
Researcher Diary
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Advantages of Qualitative Research In-depth Examination of Phenomena
(Phenomenological Study) Uses subjective information Not limited to rigidly definable variables Examine complex questions that can be impossible
with quantitative methods Deal with value-laden questions Explore new areas of research Build new theories
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Disadvantages of Qualitative Research
Subjectivity leads to procedural problems Replicability is very difficult Researcher bias is built in and unavoidable In-depth, comprehensive approach to
data gathering limits scope Labor intensive, expensive Not understood well by
“classical” researchers
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Review: Health Sciences and Nursing ResearchNon-interventional Interventional
Explorative
Descriptive Analytical
Pre-experimental
Quasi-experimenta
l
True-Experiment
- Case study- Cross-
sectional- Longitudinal- Etc.
- Cross-sectional
- Case control
- Cohort - Etc
- CRD- RBD- FD- etc
140Note: CRD-complete random design, RBD-random block design, FD- factorial
designDr. R S Mehta, MSND, BPKIHS
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Cont’d
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Relative strength of various study designs (based on level of evidence for a cause &
effect relationship)
142
Strength Design Strong Clinical trial
Cohort study Case control study Cross sectional Case series
Weak Case report
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Websites, Search Engine, and address of Journals
• www.pubmed.com• www.google.com• www.yahoo.com• www.msn.com• www.rn.com• www.who.int (WHO website)• www.randamization.com• www.tnaionline.org (TNAI Journal) • www.hellis.org (NHRC library site)• www.kumj.com.np• www.nhrc.org.np• www.uicc.org (cancer website)• www.unaids.org (HIV/AIDS website)• www.ncasc.org.np (HIV/AIDS website)• www.healthinternetwork.org (HINARI: needs password)• www.blackwell-synergy.com (need passwords)• www.doaj.org (free online journal)
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Some Popular Resource Sites for Nurses
• www.delicious.com• www.connotea.org• www.scribd.ocm• www.authorstream• www.zotero.org• www.scratch.mit.edu• www.myebook.com• www.forvo.com
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“The beautiful thing about learning is that nobody can
take it away from you.”
--BB King
Thank-You145
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Review: Health Sciences and Nursing ResearchNon-interventional Interventional
Explorative
Descriptive Analytical
Pre-experimental
Quasi-experimenta
l
True-Experiment
- Case study- Cross-
sectional- Longitudinal- Etc.
- Cross-sectional
- Case control
- Cohort - Etc
- CRD- RBD- FD- etc
146Note: CRD-complete random design, RBD-random block design, FD- factorial
designDr. R S Mehta, MSND, BPKIHS
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Cont’d
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Relative strength of various study designs (based on level of evidence for a cause &
effect relationship)
148
Strength Design Strong Clinical trial
Cohort study Case control study Cross sectional Case series
Weak Case report
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Websites, Search Engine, and address of Journals
• www.pubmed.com• www.google.com• www.yahoo.com• www.msn.com• www.rn.com• www.who.int (WHO website)• www.randamization.com• www.tnaionline.org (TNAI Journal) • www.hellis.org (NHRC library site)• www.kumj.com.np• www.nhrc.org.np• www.uicc.org (cancer website)• www.unaids.org (HIV/AIDS website)• www.ncasc.org.np (HIV/AIDS website)• www.healthinternetwork.org (HINARI: needs password)• www.blackwell-synergy.com (need passwords)• www.doaj.org (free online journal)
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Some Popular Resource Sites for Nurses
• www.delicious.com• www.connotea.org• www.scribd.ocm• www.authorstream• www.zotero.org• www.scratch.mit.edu• www.myebook.com• www.forvo.com
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“The beautiful thing about learning is that nobody can
take it away from you.”
--BB King
Thank-You151
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Developmental Research Designs
Longitudinal
• Powerful (within subject)
• Time consuming• Attrition• Testing effect
Cross Sectional
• Less time consuming
• Cohorts problem
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Research Designs/Approaches
Type Purpose Time frame
Degree of control
Examples
Experi-mental
Test for cause/effect relationships
current High Comparing two types of treatments for anxiety.
Quasi-experi-mental
Test for cause/effect relationships without full control
Current Moderate to high
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Research Designs/Approaches
Type Purpose Time frame
Degree of control
Examples
Non-experimental - corre-lational
Examine relationship between two variables
Current (cross-sectional) or past
Low to medium
Relationship between studying style and grade point average.
Ex post facto
Examine the effect of past event on current functioning.
Past & current
Low to medium
Relationship between history of child abuse & depression.
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Research Designs/ApproachesType Purpose Time
frameDegree of control
Examples
Non-experimental -corre-lational
Examine relat. betw. 2 var. where 1 is measured later.
Future -predictive
Low to moderate
Relat. betw. history of depression & development of cancer.
Cohort-sequen-tial
Examine change in a var. over time in overlapping groups.
Future Low to moderate
How mother-child negativity changed over adolescence.
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Research Designs/Approaches
Type Purpose Time frame
Degree of control
Examples
Survey Assess opinions or characteristics that exist at a given time.
Current None or low
Voting preferences before an election.
Quali-tative
Discover potential relationships; descriptive.
Past or current
None or Low
People’s experiences of quitting smoking.
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Experimental Designs Details
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Symbolism for Diagramming Experimental Designs
X = exposure of a group to an experimental treatmentO = observation or measurement of the dependent variable
If multiple observations or measurements are taken, subscripts indicate temporal order – I.e., O1, O2, etc.= random assignment of test units; individuals selected as subjects for the experiment are randomly assigned to the experimental groups
R
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Pre-Experimental Designs• Do not adequately control for the problems
associated with loss of external or internal validity
• Cannot be classified as true experiments• Often used in exploratory research• Three Examples of Pre-Experimental Designs
– One-Shot Design– One-Group Pretest-Posttest Design– Static Group Design
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One-Shot Design• A.K.A. – after-only design• A single measure is recorded after the
treatment is administered• Study lacks any comparison or control of
extraneous influences• No measure of test units not exposed to the
experimental treatment• May be the only viable choice in taste tests• Diagrammed as: X O1
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One-Group Pretest-Posttest Design
• Subjects in the experimental group are measured before and after the treatment is administered.
• No control group• Offers comparison of the same individuals before
and after the treatment (e.g., training)• If time between 1st & 2nd measurements is
extended, may suffer maturation• Can also suffer from history, mortality, and testing
effects• Diagrammed as O1 X O2
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Static Group Design• A.K.A., after-only design with control group• Experimental group is measured after being exposed
to the experimental treatment• Control group is measured without having been
exposed to the experimental treatment• No pre-measure is taken• Major weakness is lack of assurance that the groups
were equal on variables of interest prior to the treatment
• Diagrammed as: Experimental Group X O1
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Pretest-Posttest Control Group Design
• A.K.A., Before-After with Control• True experimental design• Experimental group tested before and after
treatment exposure• Control group tested at same two times without
exposure to experimental treatment• Includes random assignment to groups• Effect of all extraneous variables assumed to
be the same on both groups• Do run the risk of a testing effect
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Pretest-Posttest Control Group Design• Diagrammed as
– Experimental Group: O1 X O2
– Control Group: O3 O4• Effect of the experimental treatment equals
(O2 – O1) -- (O4 – O3) • Example
– 20% brand awareness among subjects before an advertising treatment
– 35% in experimental group & 22% in control group after the treatment
– Treatment effect equals (0.35 – 0.20) – (0.22 – 0.20) = 13%
RR
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Posttest-Only Control Group Design
• A.K.A., After-Only with Control• True experimental design• Experimental group tested after treatment exposure• Control group tested at same time without exposure
to experimental treatment• Includes random assignment to groups• Effect of all extraneous variables assumed to be the
same on both groups• Do not run the risk of a testing effect• Use in situations when cannot pretest
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Posttest-Only Control Group Design• Diagrammed as
– Experimental Group: X O1
– Control Group: O2
• Effect of the experimental treatment equals(O2 – O1)
• Example– Assume you manufacture an athlete’s foot remedy– Want to demonstrate your product is better than
the competition– Can’t really pretest the effectiveness of the remedy
RR
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Solomon Four-Group Design
• True experimental design• Combines pretest-posttest with control
group design and the posttest-only with control group design
• Provides means for controlling the interactive testing effect and other sources of extraneous variation
• Does include random assignment
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Solomon Four-Group Design• Diagrammed as
– Experimental Group 1: O1 X O2
– Control Group 1: O3 O4
– Experimental Group 2: X O5
– Control Group 2: O6
• Effect of independent variable (O2 – O4) & (O5 – O6)
• Effect of pretesting (O4 – O6) • Effect of pretesting & measuring (O2 – O5) • Effect of random assignment (O1 – O3)
RR
RR
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Quasi-Experimental Designs• More realistic than true experiments• Researchers lacks full control over the
scheduling of experimental treatments or• They are unable to randomize• Includes
– Time Series Design– Multiple Time Series Design
• Same as Time Series Design except that a control group is added
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Time Series Design• Involves periodic measurements on the
dependent variable for a group of test units• After multiple measurements, experimental
treatment is administered (or occurs naturally)
• After the treatment, periodic measurements are continued in order to determine the treatment effect
• Diagrammed as:O1 O2 O3 O4 X O5 O6 O7 O8
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Statistical Designs• Multiple experiments are conducted
simultaneously to permit extraneous variables to be statistically controlled and
• Effects of multiple independent variables to be measured
• Advantages– Can measure the effects of more than one
independent variable– Can statistically control specific extraneous
variables– Economical designs can be formulated when
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Completely Randomized Design• Involves randomly assigning treatments to
group members– Allows control over all extraneous treatments
while manipulating the treatment variable– Simple to administer, but should NOT be used
unless test members are similar, and they are also alike regarding a particular extraneous variable
– Different forms of the independent variable are called “levels.”
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Completely Randomized DesignExample
• Grocery store chain trying to motivate consumers to shop in their stores
• 3 possible sales promotional efforts
X1 = offer discount of 5% off total shopping bill
X2 = offer taste sample of selected foodsX3 = control group, no sales promotional
effort applied 174Dr. R S Mehta, MSND, BPKIHS
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Completely Randomized DesignExampleSALES PROMOTION TECHNIQUE
LEVELS 5% discount Taste samples No sales promotion
Sales, store 3 Sales, store 5 Sales, store 9
STORES Sales, store 1 Sales, store 8 Sales, store 7
Sales, store 6 Sales, store 4 Sales, store 2
Average sales Average sales Average sales
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Randomized Block Design• Randomly assigns treatments to
experimental & control groups• Test units broken into similar blocks (or
groups) according to an extraneous variable– I.e., location, age, gender, income, education,
etc.• Particularly useful when small sample sizes
are necessary
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Randomized DesignExample
• Grocery store chain trying to motivate consumers to shop in their stores
• 3 possible sales promotional effortsX1 = offer discount of 5% off total shopping
billX2 = offer taste sample of selected foodsX3 = control group, no sales promotional
effort appliedBlocks = time stores have been in operation177Dr. R S Mehta, MSND, BPKIHS
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Latin Square Design• Allows control or elimination of the effect of
two extraneous variables• Systematically blocks in 2 directions by
grouping test units according to 2 extraneous variables
• Includes random assignment of treatments to each cell in the design
• Used for comparing t treatment levels in t rows and t columns– I.e., if we have 3 treatment levels, we must have
3 rows and 3 columns 178Dr. R S Mehta, MSND, BPKIHS
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Latin Square Design
Extraneous Variable 2
A B C
Extraneous Variable 1
B C A
C A B
where A, B, & C are all treatments179Dr. R S Mehta, MSND, BPKIHS
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Latin Square Design Example
PER CAPITA INCOME
TIME IN OPERATION
High Medium Low
< 5 years X1 X2 X3
5 – 10 years X2 X3 X1
> 10 years X3 X1 X2
180Dr. R S Mehta, MSND, BPKIHS
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Factorial Design• Used to examine the effects that the
manipulation of at least 2 independent variables (simultaneously at different levels) has upon the dependent variable
• The impact that each independent variable has on the dependent variable is referred to as the main effect
• Dependent variable may also be impacted by the interaction of the independent variables. This is called the interaction effect 181Dr. R S Mehta, MSND, BPKIHS
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Factorial Design Example• Grocery store chain wants to use 12 of its stores to
examine whether sales would change at 3 different hours of operation and 2 different types of sales promotions
• Dependent variable is change in sales• Independent variables
– Store open 6 am to 6 pm– Store open 6 am to midnight– Store open 24 hours/day– Sales promotion: samples for a free gift– Sales promotion: food samples
• Called a 3 x 2 factorial design• Need 6 experimental groups (3 x 2 = 6)
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Factorial Design ExampleHOURS OF OPERATION
SALES PROMOTION
6 am – 6 pm 5 am – midnight 24 hours
Gift stamps
Food samples
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Test Marketing• Controlled experiment conducted on a small
segment of the target market• Major objectives
– Determine how well products will be accepted in the marketplace
– Determine how changes in marketing mix will likely affect product success
• Major reason for test marketing is risk reduction– Lose $ 1 million in test market or $ 50 million on product
failure?• Problems
– Expense– Time– Competitors can disrupt 184Dr. R S Mehta, MSND, BPKIHS
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Factors to Consider• Population size• Demographic composition• Lifestyle considerations• Competitive situation• Media coverage & efficiency• Media isolation• Self-contained trading area• Overused test markets• Loss of secrecy
185Dr. R S Mehta, MSND, BPKIHS