data analysis, walaa elleithey

8/2/2019 Data Analysis, Walaa Elleithey

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University of AlexandriaFaculty of Nursing

Doctorate Programme Research 2

2012

SUPERVISED BY:

Prof. Dr. Mervat El Genedi

PREPARED BY:

Walaa elleithy

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Goal

At the end of this seminar the doctorate students willbe able to:Understand Qualitative data analysis and two common approaches.

Intended learning outcomes:

A.Knowledge and understanding:

1. Clarify of the concept ofqualitative data analysis

2. Describe the steps of grounded theory approach.

3. Explore main types of data analysis

4. Explore aims of qualitative data analysis.

B.Intellectual skills:

1. Clarify the relationship between grounded theory approach and

framework approach .

2. Compare approaches in analysing qualitative data

C.Professional and practical skills:

1- Code and develop categories in qualitative data

analysis

D.General and transferable skills:

1. Participate in developing a new qualitative research analysis.

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Agenda

Introduction

What is qualitative data?

What is analysis?

Aim of qualitative data

Inductive and deductive approch

Stages in Qualitative Data Analysis

a) Familiarisation

b) Transcription

c) Organisation

d) Coding

Analysis (Grounded Theory)

Analysis (Framework)

e) Report writing

Qualitative Data Software

References

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Introduction

Analysing qualitative data is not a simple or quick task. Done

properly, it is systematic and rigorous, and therefore labour-intensive and

time-consuming. The major element of qualitative analysis is to find, build,

clarify, illustrate and explain an argument or issue. The analysis should take

the form of a research essay containing certain expected elements: How you

introduce them and sequence the elements must be logical and help readers

to get it.

Qualitative Data

is mostly in the form of words, phrases, sentences and may include visual

images, audio and video recordings. Qualitative data is a mass of words

obtained from recordings of interviews, fieldnotes of observations, and

analysis of documents as well as reflective notes of the researcher. This mass

of information have to be organised, summarised, described and interpreted

Qualitative Data Analysis (QDA)

is the range of processes and procedures whereby we move from the

qualitative data that have been collected into some form of explanation,understanding or interpretation of the people and situations we are

investigating.

Aims of qualitative analysis

1. Understand the phenomenon

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2. Go beyond reporting move towards INTERPRETATION

3. Identify themes and sub-themes

Generally, since numbers are not used, the qualitative researcher looks

for categories or themes from the raw data to describe and explain

phenomena. analyses the relationships and patterns between the categories or

themes that have been identified. using two approaches:

o Inductively whereby the categories or themes are allowed to

emergefrom the data gradually. This has been termed as grounded

theory.

o Deductively whereby from the very beginning or half-way through

you begin to identify the categories or themes and fit the data into the

categories and themes which is later interpreted.

Main Types Of Qualitative Analysis.

Characteristics of language e.g. content analysis

Discovery of regularities e.g. grounded theory

Comprehension of meaning e.g. phenomenology

Content Analysis

There are several ways to conduct content analysis of text: from grounded

theory, without any preconceived ideas, to identifying only somebody elses

categories e.g., when the researchers have to explore a set of questions,

predetermined by an external funding body.

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In grounded theory the categories emerge through a process of inductive

reasoning, rather than the data being allocated to predetermined categories.

Ideally, the researchers start the data gathering and subsequent analyseswithout any defined ideas on what they will find. The analyses are

undertaken following

Constant Comparative Method Steps:

Immersion producing detailed transcriptions

Categorization assigning categories

Reduction grouping categories in themes

Triangulation checking themes against all transcripts (preferably with

other people)

Interpretation making sense of data with new model or established theory

these two approaches Grounded theory approach and Framework

analysis approach.

It usually begins with familiarisation of the data, transcription, organisation,

coding, analysis (grounded theory or framework analysis) and reporting

(though the order may vary).

Stages in qualitative data analysis

Analysis

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STAGES IN QUALITATIVE ANALYSIS

Familiarisation Transcription Organisation

Grounded

theory

Report

Writing


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Analysis

Phase 1. Familiarisation

You have massive amount of material and you may

have to listen to tapes and watch video material, read

and re-read the field notes, make memos and

summaries before formal analysis begins. This is

especially important when besides you, others are also

involved in data collection. You have got to be familiar

with the field notes they made (perhaps trying to

decipher their handwriting!).

Phase 2. Transcription

converting audio recorded data or handwritten fieldnotes obtained from

interviews and observations into verbatim form (i.e. written or printed) for

easy reading. Why? If you were to analyse direct from an audio recording or

fieldnotes, there is the likelihood that you may include those sections that

seem relevant or interesting to you and ignore others. Transcription involves

judgments about what level of detail to choose (e.g. omitting non-verbal

dimensions of interaction), data interpretation (e.g. distinguishing 'I don't,no' from 'I don't know')

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Field notes

Interview

Transcript

Coding

Framework

analysis


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???You should not forget to include non-verbal cues in the transcript such

as silence (which may indicate embarrassment or emotional distress), pause

for thought (such as wellerI suppose.) laughter, gestures (which may

add meaning to the spoken word) and so forth. If someone else is

transcribing your material, make sure to tell him or her how much of this

non-verbal information to include.

Phase 3. ORGANISATION

organise data into sections that is easy to retrieve.

Example, in your study you interviewed 10 teachers

(30 minutes each) on their opinion about the leadership

style of their principal. It is advisable that you give each

teacher a pseudonym (e.g. Elvis, Michael, Dina not

their real name) or referred to by a code number (e.g.

T1, T2..T10). You need to keep a file that links the

pseudonym or code number to the original informants which should be kept

confidential and destroyed after completion of the research. Names and other

identifiable material should be removed from the transcripts.

Phase 4. CODING

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looking for similar words or phrases in the transcripts. Once you have these

phrases, put them into categories/themes, that they can easily be retrieved at

a later stage for further comparison and analysis. Codes can be based on:*Themes, Topics *Ideas, Concepts

*Terms, Phrases *Keywords

The codes are given meaningful names that gives an indication of the

idea or concept that underpins the theme or category. This process of coding

(associating labels with the text, images etc) involves close reading of the

text (or close inspection of the video or images). If a theme is identified from

the data that does not quite fit the codes that are already existing then a

new code is created.

EXAMPLE: Strauss and Corbin (1998) suggest open coding.

Open coding is where you sweep through the data and marking the text

Example of an interview with a teacher describing the behaviour of his

principal at staff meetings with teachers in the school.

the following codes are assigned.

B1 hot tempered; B2 lost his cool

B3 refused to listen B4 just went on and on

B6 scolds B7 ridiculed for questioning

B8 one man show

Next recode the eight descriptions into one or two categories. B3 and B8

could be recoded to A1 and assigned theme autocratic.

Coding Techniques

The following are two techniques of coding:

1- Cut and Paste cut your transcripts into smaller unit of

analysis which could be individual words, phrases, sentences or

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paragraphs. paste these text units on to cards which you could sort easily.

Keep in mind that each text unit needs to be traceable to its original context.

2-Colour Code highlight text units to underline units of text. There could bea problem when there are hundreds of text units and you will need hundreds

of colours which could pose a problem differentiating the colours . Is the

choice if you do not have too many categories or text units.

Combinationperhaps a preferred technique would be combination

Step 5. ANALYSIS

A) Grounded Theory Inductive Approach

is an inductive approach in the analysis of qualitative data in which

theory is systematically generated from data. However, many studies in

medicine, public health and in nursing), has been widely adopted as a

procedure for conceptualising and analysing data. it allows for the theory to

emergefrom the data through a process of rigorous analysis.

The grounded theory approach is different from the framework

approach in analysing qualitative data. The grounded theory approach

emphasises on theory as the final output of research. The framework

approach in data analysis may stop at the level of description or simple

interpretation. The aim of grounded theory is theoretical development.

which is increasingly commonly used in health-related research.

grounded theory approach,

the plausible (likely or probable) relationships between sets of categorieswhich have emerged from data analysed. So, theory is a statement about

possible relationships among categories about a phenomenon that helps one

understand his or her social world. Note that a theory is not an absolute

truth but rather a tentative explanation of a phenomenon (e.g., adolescents

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damage public property in an effort to seek attention because of low self-

esteem).

The Main Feature Of The Grounded Theory

1. use of the constant comparison technique. categories or concepts that

emerge from one stage of analysis are compared with categories or

concepts that emerge from the previous stage.2. The researcher continues with this technique until what is called

theoretical saturation is reached or no new significant categories or

concepts emerge.

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Word

WordWord

WordPhrase

Phrase

Phrase

PhraseRAW

DATA

Identifyand

Categorise

Data

CATEGORIES EMERGE FROM

THE DATA

THEORY EMERGES SHOWING RELATIONSHIPS

AMONG THE CATEGORIES

Category #1 Category #2 Category #3


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3. procedure is cyclical involving frequent revisiting of data in the

light of emergence of new categories or concepts as data analysis

progresses.4. The theory that develops is best seen as provisional until proven

by the data and validation from others.

Grounded Theory Analysis

1. open coding (initial familiarization with the data)

2. delineation of emergent concepts

3. conceptual coding (using emergent concepts)

4. refinement of conceptual coding schemes

5. clustering of concepts to form analytical categories

6. searching for core categories

7. core categories lead to identification of core theory

8. testing of emerging theory by reference to other research and to

social/cultural/economic factors that affect the area of study.

B) Framework Analysis Deductive Approach

1. framework analysis was explicitly developed for applied research, the

findings and recommendations of research need to obtained with a

short period to be adopted.

2. This approach allows the researcher to set the categories and themes

from the beginning of the study. However, this approach also allows

for categories and themes that may emerge during data analysis which

the researcher had not stated at the beginning of the study.

3. specific pieces of data are identified which correspond to the different

themes or categories.

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Example from medicine. You may want to know, for instance, about how

people who had had a heart attack conceptualise the causes of the attack.

From existing literature, you may know that these can be divided intophysical causes, psychological causes, ideas of luck, genetic inheritance and

so forth. You interview people who have had a heart attack and from the

interview transcript you search the data for material that could be coded

under these headings.

Using the headings, you can create charts of your data so that you can

easily read across the whole dataset.

Charts can be either thematic for each theme or category across all

respondents (cases) or by casefor each respondent across all themes.

Thematic Chart

THEME Case 2 Case 3

Psychological

cause

The stress at office is too

much. Got to work late

Business was bad.

Had to close shop

Case Chart

Theme 1

Genetic inheritance

Theme 2

Physical cause

CASE 1

My younger brother and

father died of a heart attack

I hardly do any

exercise. I too busy to

do any exercise

Key Stages Of Framework Analysis

1. Familiarisation (reading of the data.)

2. Identifying a thematic framework(initial coding framework)

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3. coding (using numerical or textual codes to identify specific pieces

of data which correspond to differing themes)

4. Charting (thematic or cases)5. Mapping and Interpretation (searching for patterns,

associations, concepts, and explanations in your data, aided by visual

displays and plots).

Step 6: REPORT WRITING

a) Introducing your Study

1. Begin with something interesting, e.g., a quote or story, to

capture the reader's interest.

2. Introduce your question or curiosity. What is it that you want to

know or understand? How did you get interested in the topic?

3. Tell why there's a need for the study. Cite relevant literature

that calls for the need for the research in this area, or

demonstrates the lack of attention to the topic. In your own

words, describe how you think this study will be useful.

4. Describe the intended audience for your research (e.g., the

public, family therapists).

b) Research Method

1. Identify and generally describe your research method (e.g., ethnographic

field study, single case study), and your research procedures (e.g., long

interviews, observation).

2. Cite the major authors who have described your research method.

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3. Explain how you will selected your subjects and gained entry into the

research context (if relevant).

4. Describe the procedures you took to protect the rights of your subjects(e.g., informed consent, human subjects approval, debriefing).

5. Describe the kind of relationship you had with the subjects. Will you be

neutral, collaborative, objective?

6. Describe the kind of data you collected (e.g., field notes from memory,

audio tapes, video tapes, transcripts of conversations, examination of

existing documents, etc.).

7. Describe the procedures used in data collection. If interviews were used,

list your question(s) or attach as an appendix. Describe any equipment

used.

8. Describe the procedures you used to keep track of the research process.

i.e. your audit trail.

Process notes: Day to day activities, methodologicalnotes, decision making procedures.

Materials relating to intentions and reactions: personal

notes about motivations, experiences with informants, etc.

Instrument development information: revisions of

interview questions.

9. Describe your data analysis procedures (coding, sorting, etc.)?

Data reduction: Write-ups of field notes, transcription

procedures and conventions, computer programs used, etc.

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Data reconstruction: development of categories, findings,

conclusions, connections to existing literature, integration of concepts.

10.Describe how you ensure "reliability" and "validity." For mention

whether you used triangulation, member checking, peer debriefing,

auditing.

11.Describe how you reviewed the literature and how it has influenced the

way you approached the research.

12. Discuss how your previous experience with your topic has influenced the

way you have conceptualized this research.

13. Summarize references

The bottom line is credibility. It refers to the accuracy of your

description as show in your report... If you want to convince your reader that

the findings you obtained are credible (or accurate) you need to state

precisely the parameters of the study. Parameters involves who was studied,

where and when, and methods used. If you are able to state these aspects

clearly, you enhance the credibility of the study.

Qualitative Data Software

The most commonly used packages:

1. ETHNOGRAPH.

2. ATLASTi.

3. NVIVO

4. HyperRESEARCH

5. NUD*IST.

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The last two packages are examples for having theory- building capability,

and all of packages have coding ability, retrieving data that relates to

specific codes, which can then be arranged to show relationships asdetermined by the researcher. The benefits of using computer-assisted data

analysis aren't necessarily linked to time- saving, but there are advantages to

the researcher in the way packages organize and store information.

REFERENCES

1. Glaser, B. and Strauss, A. (1967): The discovery of grounded theory.

London: Weidenfield & Nicolson.

2. Lacey, A. & Luff, D. (2001). Trent focus for research and

development in primary health care: An introduction to qualitative

analysis. London: Trent Focus.

3. Lewins, A., Taylor, C. & Gibbs, G. (2005). What is qualitative data

analysis? School of Human & Health Sciences, University of

Huddersfield. United Kingdome.

4. Strauss, A. (1987). Qualitative analysis for social scientists. New

York: Cambridge University Press.

5. Strauss, A. and Corbin, J. (1990). Basics of qualitative research:

Grounded theory procedures and techniques. London: Sage

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6. Russell, B. (1996) Qualitative Data, Quantitative Analysis. Cultural

Anthropology Methods Journal, Vol. 8 no. 1, 9-11.

http://web.missouri.edu/~anthgr/papers/Bernardqualquant.htm

7. Chapter15: Qualitative Data Analysis

http://www.southalabama.edu/coe/bset/johnson/dr_johnson/lectures/le

c17pd

8. Lindee Morgan. Module: Qualitative Data Analysis

http://comm2.fsu.edu/programs/commdis/ddseminar/QualitativeAnaly

sis.

9. Donald Ratcliff. 15 Methods of Data Analysis in Qualitative Researchhttp://www.vanguard.edu/uploadedFiles/faculty/dratcliff/qualresource

s/15methods.pdf

10. John Carney and Joseph Joiner. Categorising, Coding and

Manipulating Qualitative Data Using the WordPerfect Word

Processor. The Qualitative Report. 1997. 3(2)

http://www.nova.edu/sss/QR/QR3-1/carney.html

11. Thorne, S. (2000): Data analysis in qualitative research.Evid BasedNurs ;3:68-70 doi:10.1136/ebn.3.3.68

12. Gibbs, G. (2002) Qualitative data analysis: explorations with NVivo.

London: Open University Press.

13. Glaser, B. G. and Strauss, A. L. (1967) The discovery of grounded

theory: strategies for qualitative research. New York: Aldine de

Gruyter.

14. Barry, Christine (1998). Choosing qualitative data analysis software:

Atlas/ti and Nudist compared.Sociological Research Online, 3(2),

http://www.socresonline.org.uk.socresonline/3/3/4.html.

15. Fielding, Nigel, & Lee, Raymond (1998) (Eds.). Computer analysis &

qualitative research. Thousand Oaks: Sage.

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16. Fielding, Nigel, & Lee, Raymond (1993) (Eds.). Using computers in

qualitative research (revised & updated). Thousand Oaks: Sage.

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