Qualitative_data_analysis

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INTRODUCTION 7 First of all, I take a rather eclectic view of the sources of qualitative data. The association of qualitative data with unstructured methods is one which I challenge in the following chapter. Problems of conceptualization are as important in surveys as in any other research methods, and problems of interpretation and classification are as important to survey data as in any other context (Marsh 1982). Secondly, I take a similarly eclectic view of qualitative analysis. Analysis aimed at describing situations or informing policy seems to me no less legitimate and worthwhile than analysis geared to generating theory. I also assume that we may be as interested in identifying and describing ‘singularities’, in the sense of unique events or cases, as in identifying and explaining regularities and variations in our data. Throughout the book, I assume that qualitative analysis requires a dialectic between ideas and data. We cannot analyse the data without ideas, but our ideas must be shaped and tested by the data we are analysing. In my view this dialectic informs qualitative analysis from the outset, making debates about whether to base analysis primarily on ideas (through deduction) or on the data (through induction) rather sterile (Chapter 5). This dialectic may be less disciplined than in the natural sciences, where experiment and quantitative measurement provide a firmer basis for examining evidence; but the search for corroborating evidence is nevertheless a crucial feature of qualitative analysis (Chapter 14). It is also a vital element in producing an adequate as well as an accessible account (Chapter 15). Thirdly, I take a pragmatic view of analytic procedures (cf. Giarelli 1988). My main aim is to give a practical introduction to analytic procedures. The book describes a range of procedures we can follow for managing data (Chapter 6), reading and annotating (Chapter 7), categorizing (Chapters 8, 9 and 10), linking data (Chapter 11), connecting categories (Chapter 12) and using maps and matrices (Chapter 13). While these procedures are presented sequentially, in practice the mix and order of procedures adopted in qualitative analysis will vary. The choice of any particular permutation of procedures depends upon factors like the characteristics of the data, the objectives of the project, the predilections of the researchers, and the time and resources available to them. If we consider qualitative data analysis (somewhat misleadingly) in terms of a logical succession of steps leading from our first encounters with the data through to the production of an account, then the various steps considered in this book can be depicted as in Figure 1.1. Because of its importance in conceptualizing data, three chapters are devoted to the tasks of categorizing, and a further two chapters to ways of making connections between categories. The intervening step (Chapter 11) is concerned with linking data, as an innovative technique for overcoming the fragmentation of data produced by categorization, and providing a firm basis for identifying conceptual connections between categories.
8 QUALITATIVE DATA ANALYSIS Figure 1.1 The steps involved in data analysis—chapter by chapter As my aim is to provide an accessible and practical guide to analytic procedures, I have avoided burdening the text with references to related work. With respect to existing literature, the three chapters on categorizing data and the preceding chapter on reading and annotating draw mostly on the work of Strauss (1987) and Strauss and Corbin (1990), though I have made no effort to remain within the restrictive confines of grounded theory. Patton (1980) and Becker and Geer (1982) also review the main analytic procedures involved. The discussion of associating categories and mapping data in Chapters 12 and 13 draws upon work by Bliss and her colleagues (1983) and by Miles and Huberman (1984). The related discussion of linking data derives mainly from my own work, although I am indebted to Sayer (1992) for an epistemological review of the relevant issues. The chapter on corroborating evidence draws on work by Becker and Geer (1982). None of these texts relates analytic procedures to computing techniques, and for further discussion the reader should refer to the works by Tesch (1990) and Fielding and Lee (1991). Finally, a word on language. The proliferation of different research styles and software packages has led to marked inconsistencies in the terminology used by qualitative analysts. For example, when bits of data are demarcated in some way for
Page 2 and 3: Qualitative data analysis Learning
Page 4 and 5: First published 1993 by Routledge 1
Page 6 and 7: Glossary 283 References 285 Index 2
Page 8 and 9: 9.1 Categorizing data—1 120 9.2 C
Page 10 and 11: 3.1 Personal ads 42 5.1 ‘The libr
Page 12 and 13: Preface A new book on qualitative d
Page 14 and 15: analyse humour from any number of p
Page 16 and 17: Q. What colour is snow? A. White. C
Page 18 and 19: INTRODUCTION 3 approaches, interest
Page 20 and 21: INTRODUCTION 5 qualitative methods.
Page 24 and 25: INTRODUCTION 9 the purposes of anal
Page 26 and 27: WHAT IS QUALITATIVE DATA? 11 distan
Page 28 and 29: WHAT IS QUALITATIVE DATA? 13 contem
Page 30 and 31: WHAT IS QUALITATIVE DATA? 15 ‘ric
Page 32 and 33: classified. Take the example in Ill
Page 34 and 35: Figure 2.1 Describing a bit of data
Page 36 and 37: WHAT IS QUALITATIVE DATA? 21 home;
Page 38 and 39: Figure 2.4 Nominal variable with mu
Page 40 and 41: Figure 2.6 Interval variable with f
Page 42 and 43: ILLUSTRATION 2.2 EXAMPLE OF A GRADI
Page 44 and 45: WHAT IS QUALITATIVE DATA? 29 what a
Page 46 and 47: Chapter 3 What is qualitative analy
Page 48 and 49: Figure 3.2 Three aspects of descrip
Page 50 and 51: WHAT IS QUALITATIVE ANALYSIS? 35 co
Page 52 and 53: WHAT IS QUALITATIVE ANALYSIS? 37 en
Page 54 and 55: WHAT IS QUALITATIVE ANALYSIS? 39 Th
Page 56 and 57: CLASSIFICATION WHAT IS QUALITATIVE
Page 58 and 59: nature; photograph preferred but no
Page 60 and 61: WHAT IS QUALITATIVE ANALYSIS? 45 vi
Page 62 and 63: WHAT IS QUALITATIVE ANALYSIS? 47 Fi
Page 64 and 65: Figure 3.6 Formal and substantive c
Page 66 and 67: WHAT IS QUALITATIVE ANALYSIS? 51 ne
Page 68 and 69: WHAT IS QUALITATIVE ANALYSIS? 53 If
Page 70 and 71: Figure 3.10 Qualitative analysis as
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Chapter 4 Introducing computers ‘
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ecording of an index of information
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Figure 4.1 A link between text held
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Computer transformations • Search
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Chapter 5 Finding a focus A Zen sto
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FINDING A FOCUS 67 Sheila The solic
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FINDING A FOCUS 69 to reflect upon
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For example, here are some question
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Transposition: Doctor: ‘I’m afr
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Figure 5.2 Main themes for analysin
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Chapter 6 Managing data Piles of pa
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MANAGING DATA 79 setting, by source
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MANAGING DATA 81 Interviewer Maybe
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Figure 6.1 Case documents kept in a
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MANAGING DATA 85 ‘Show the full r
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Chapter 7 Reading and annotating Ac
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• Official/bureaucratic commitmen
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READING AND ANNOTATING 91 women wer
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Techniques for interactive reading
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we can write our comment on a separ
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Figure 7.1 Relating data to key the
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READING AND ANNOTATING 99 may retur
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CREATING CATEGORIES 101 types of ph
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CREATING CATEGORIES 103 conceptual
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CREATING CATEGORIES 105 Categorizat
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Table 8.1 Alternative category list
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This is only a starting point. Our
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CREATING CATEGORIES 111 undertaking
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Figure 8.2 Weighing up the degree o
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CREATING CATEGORIES 115 Although co
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CREATING CATEGORIES 117 for an adeq
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CREATING CATEGORIES 119 well as con
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Figure 9.2 Categorizing data—2 Fi
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are entitled to expect some consist
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ASSIGNING CATEGORIES 125 we ought t
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ASSIGNING CATEGORIES 127 the data.
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have annotated this data. Suppose w
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ASSIGNING CATEGORIES 131 suddenly t
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• What generally constitutes a
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Databits Categories 5. Now she is u
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Chapter 10 Splitting and splicing T
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Using Hypertext linking, whenever n
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SPLITTING AND SPLICING 141 databits
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Category Subcategories Suffering Di
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Figure 10.1 Levels of subclassifica
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ILLUSTRATION 10.5 SUBDIVIDING DATAB
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Figure 10.2 Initial relationships b
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If we want to make this change, it
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Figure 10.5 Reassessing relationshi
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SPLITTING AND SPLICING 155 Although
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Figure 10.8 Comparing subcategories
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Figure 10.9 Shifting the analytic e
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Chapter 11 Linking data Categorizin
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Figure 11.2 Multiple hyperlinks bet
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example, we may ask what it is abou
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Figure 11.5 Linking and categorizin
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Figure 11.7 An explanatory link bet
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Table 11.2 Multiple links between d
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our reasons for making decisions an
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Figure 11.11 Conditional and causal
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Chapter 12 Making connections Imagi
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Figure 12.1 The difference between
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Table 12.1 Concurrence between cate
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Table 12.4 Boolean operators for ca
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From Table 12.6 we can tell that mo
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Notice how this cross-tabulation co
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substantive connections between cat
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Figure 12.5 Following a trail of di
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Figure 12.7 Retrieving chronologica
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This approach is very exploratory,
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MAKING CONNECTIONS 197 Table 12.10
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MAKING CONNECTIONS 199 a consequenc
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Chapter 13 Of maps and matrices A n
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Table 13.1 Comparing information ac
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OF MAPS AND MATRICES 205 [In a calm
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Table 13.5 Data indices by case and
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Table 13.7 Recoding data to express
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Table 13.11 Cross-tabulating ‘occ
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Figure. 13.4 The history of the uni
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Figure 13.7 Incorporating detail by
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Figure 13.10 Comparing differences
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Figure 13.13 Adjusting scope of mos
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Figure 13.17 Comparing strength of
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Figure 13.20 Identifying positive a
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OF MAPS AND MATRICES 225 undercurre
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Chapter 14 Corroborating evidence
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CORROBORATING EVIDENCE 229 There is
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CORROBORATING EVIDENCE 231 describe
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CORROBORATING EVIDENCE 233 of these
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Figure 14.1 Concurrence between cat
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CORROBORATING EVIDENCE 237 possibil
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CORROBORATING EVIDENCE 239 that the
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CORROBORATING EVIDENCE 241 seductiv
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CORROBORATING EVIDENCE 243 research
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Chapter 15 Producing an account ‘
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PRODUCING AN ACCOUNT 247 An analysi
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Figure 15.2 The whole is greater th
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Figure 15.3 Tree diagrams represent
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PRODUCING AN ACCOUNT 253 associatio
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worrying unduly about the connectio
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Figure 15.5 Different writing strat
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PRODUCING AN ACCOUNT 259 the vibrat
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Figure 15.7 Procedures for assignin
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PRODUCING AN ACCOUNT 263 consistent
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Table 15.1 Databits assigned to cat
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Table 15.3 Distribution of response
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PRODUCING AN ACCOUNT 269 To be subj
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PRODUCING AN ACCOUNT 271 analysts t
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Figure 16.3 Analysis as an iterativ
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CONCLUSION 275 empirical analysis o
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Appendix 1 ‘If the Impressionists
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APPENDIX 1 279 though it had been o
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Appendix 2 Software The reader look
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Glossary Associating categories the
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References Allen, Woody (1978) ‘I
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REFERENCES 287 Sperber, Dan and Wil
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Capra, F. 29, 64, 99 case studies 1
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Galtung, J. 14 Geer, B. 7, 8, 29, 5
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connections; description qualitativ
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