Qualitative data analysis : practical strategies

Title:

Personal Author:

Bazeley, Patricia

Publication Information:

London : SAGE, c2013

Physical Description:

xxiii, 444 p. : ill. ; 24 cm.

ISBN:

9781849203029

9781849203036

Subject Term:

Qualitative research -- Data processing

Social sciences -- Research -- Data processing

Social sciences -- Statistical methods

Available:*

Library	Item Barcode	Call Number	Material Type	Item Category 1	Status
Searching... PSZ JB	30000010303635	H61.3 B396 2013	Open Access Book	Book	Searching... Unknown
Searching... PSZ KL	33000000001109	H61.3 B396 2013	Open Access Book	Book	Searching... Unknown

Summary

Written by an experienced researcher in the field of qualitative methods, this dynamic new book provides a definitive introduction to analysing qualitative data.

It is a clear, accessible and practical guide to each stage of the process, including:

- Designing and managing qualitative data for analysis

- Working with data through interpretive, comparative, pattern and relational analyses

- Developing explanatory theory and coherent conclusions, based on qualitative data.

The book pairs theoretical discussion with practical advice using a host of examples from diverse projects across the social sciences. It describes data analysis strategies in actionable steps and helpfully links to the use of computer software where relevant.

This is an exciting new addition to the literature on qualitative data analysis and a must-read for anyone who has collected, or is preparing to collect, their own data.

Summary

Written by an experienced researcher in the field of qualitative methods, this dynamic new book provides a definitive introduction to analysing qualitative data.

It is a clear, accessible and practical guide to each stage of the process, including:

- Designing and managing qualitative data for analysis

- Working with data through interpretive, comparative, pattern and relational analyses

- Developing explanatory theory and coherent conclusions, based on qualitative data.

This is an exciting new addition to the literature on qualitative data analysis and a must-read for anyone who has collected, or is preparing to collect, their own data.

Author Notes

Pat Bazeley is Director of Research Support P/L and Associate Professor at the University of New South Wales.

List of figures	p. x
List of tables	p. xiv
List of boxes	p. xv
About the author	p. xix
Preface	p. xx
Software, symbols, and sample data	p. xxi
Acknowledgements	p. xxiii
Part 1 Preparing the Way: Laying the Foundations for Analysis	p. 1
1 Foundations for thinking and working qualitatively	p. 3
Thinking qualitatively	p. 3
Thinking methods (and methodology)	p. 8
Working qualitatively	p. 12
Working qualitatively - using software	p. 17
Foundations for working qualitatively	p. 19
Working qualitatively - implications for analysis	p. 27
Writing about foundations	p. 28
Exercises	p. 29
Further reading	p. 30
2 Designing for analysis	p. 32
Design: giving form to ideas Focusing the study	p. 32
Designing for data that can be analysed	p. 47
Planning for quality and credibility of conclusions	p. 55
Putting it all together	p. 58
Writing about design	p. 60
Exercises	p. 61
Further reading	p. 61
3 Managing and preparing data for analysis	p. 63
Before data collection	p. 63
Keeping organised, available, and usable data records	p. 64
Recording and preparing data for analysis	p. 67
The importance of context	p. 81
Recording sample details for analysis	p. 84
Checks and balances for data	p. 89
Managing relationships in the research team	p. 90
Writing about data management	p. 91
Exercises	p. 91
Part 2 Working with Data: A Pathway into Analysis	p. 93
Data samples: becoming and being a researcher	p. 95
4 Read, reflect, and connect: initial explorations of data	p. 101
Read, and read again	p. 101
Write as you read	p. 102
Reflect in a research journal and/or memos	p. 102
Annotate text	p. 105
Purposeful play: preliminary explorations of each data source	p. 106
Explore the storylines	p. 113
Exploring context	p. 119
Identify relevant categories and concepts	p. 120
Involving participants in early analysis	p. 121
Refocus, ready for the next phase	p. 122
Writing about preliminary analysis	p. 123
Exercises	p. 124
Further reading	p. 124
5 Codes and coding: principles and practice	p. 125
Using codes to work with data	p. 125
Practical tools for coding	p. 132
Methods decisions in coding	p. 142
Issues of validity and reliability in coding	p. 148
Managing the process of coding	p. 152
A final reminder: codes and coding in context	p. 154
Writing about coding processes	p. 155
Exercises	p. 155
Further reading	p. 156
6 Naming, organising, and refining codes	p. 157
What's in a name?	p. 157
Naming broad topic areas	p. 159
Naming codes to capture substance and meaning	p. 160
Automating coding	p. 172
Developing a coding system	p. 177
Reviewing and refining codes and the coding structure	p. 185
Writing about codes	p. 185
Exercises	p. 186
Further reading	p. 187
7 Alternative approaches to breaking open and connecting data	p. 188
Building on cases	p. 188
Themes as an alternative to codes?	p. 190
Focus on interaction: working with focus group data	p. 198
Focus on stories and accounts: identifying structure, interpreting meaning	p. 200
Focus on discourse: the intersubjective space	p. 216
The value of case-based approaches	p. 220
Writing about your use of case-based, thematic, and narrative methods	p. 221
Exercises	p. 221
Further reading	p. 221
Part 3 Describe, Compare, and Relate: Moving on From Codes and Themes	p. 223
8 Describing, evolving, and theorising concepts	p. 227
Describing categories and concepts (or themes) as a step in analysis	p. 227
Evolving concepts with analytic, meta-, or pattern codes	p. 232
Theorising concepts	p. 238
Writing about describing and analysing concepts	p. 251
Exercises	p. 251
Further reading	p. 253
9 Comparative analyses as a means of furthering analysis	p. 254
Why compare?	p. 254
The comparative process	p. 256
Managing data to make subgroup, contextual, or case comparisons	p. 258
Comparing concepts or categories across groups or situations	p. 263
Comparing cases	p. 272
Interpreting comparative analyses	p. 279
Writing about comparisons	p. 280
Exercises	p. 281
Further reading	p. 281
10 Relational analyses	p. 282
Coding and connecting working together	p. 282
Investigating relational patterns	p. 284
Cross-case analyses	p. 285
Visual strategies for cross-case analyses	p. 290
Identifying patterns of association between sets of related phenomena, using coded data	p. 296
Relating data to a theoretical model	p. 306
Investigating relationships between specific categories and concepts	p. 308
Writing about exploring and testing relationships in data	p. 321
Exercises	p. 322
Further reading	p. 323
Part 4 Bringing it Together: Moving Toward Climax and Closure	p. 325
11 If...then...is it because? Developing explanatory models and theories	p. 327
Analytic progression	p. 328
Explanatory theory as a goal of research	p. 329
Foundations for explanatory theory	p. 331
Logic-based questioning: finding the major premise	p. 337
Puzzle solving with 'conjectures and refutations'	p. 339
Case-based strategies	p. 345
Theoretical development and integration in grounded theory	p. 355
Visual tools for theory building	p. 358
Writing about your developing theory	p. 369
Further reading	p. 369
12 Developing coherent understanding	p. 371
Coherent understanding?	p. 371
Coherence through description	p. 374
Theoretical coherence	p. 384
Coherence through display	p. 392
A collection of tips and tricks for bringing it together	p. 399
Writing about developing coherence	p. 400
Further reading	p. 400
13 Defending and extending: issues of quality and significance	p. 401
The issue of quality	p. 402
Generalisation and transferability	p. 410
Theoretical extension	p. 411
Audiences and representation	p. 415
A final reflection	p. 419
Writing about quality and significance	p. 420
Exercises	p. 420
Further reading	p. 421
After-Words	p. 422
References	p. 423
Index	p. 441

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Table of Contents