1. REAL WORLD RESEARCH THIRD EDITION Chapter 17: The Analysis and Interpretation of Qualitative Data 1©2011 John Wiley & Sons Ltd.

2. Common features of qualitative data analysis giving labels (‘codes’) to chunks (words, phrases, paragraphs, or whatever adding comments, reflections, etc. (commonly referred to as ‘memos’) going through the materials trying to identify similar phrases, patterns, themes, relationships, sequences, differences between subgroups, etc. continued … 2©2011 John Wiley & Sons Ltd.

3. Common features of qualitative data analysis - continued using these patterns, themes, etc. to help focus further data collection gradually elaborating a small set of generalizations that cover the consistencies you discern in the data, and linking these generalizations to a formalized body of knowledge in the form of constructs or theories (based on Miles and Huberman, 1994, p. 9) 3©2011 John Wiley & Sons Ltd.

4. Ways of keeping track of information These include the use of: Session summary sheets Document sheets Memoing The interim summary 4©2011 John Wiley & Sons Ltd.

5. Phases of thematic coding analysis 1 Familiarizing yourself with your data 2 Generating initial codes 3 Identifying themes 4 Constructing thematic networks 5 Integration and interpretation. 5©2011 John Wiley & Sons Ltd.

6. Advantages of thematic coding analysis 1 Very flexible, can be used with virtually all types of qualitative data 2A relatively easy and quick method to learn and use 3 Accessible to those with little experience of qualitative research 4The results of the analysis can be communicated without major difficulties to practitioners, policy makers and an educated general public continued … 6©2011 John Wiley & Sons Ltd.

7. Advantages of thematic coding analysis - continued 5 A useful method to employ when working within a participatory research paradigm 6Provides a means of summarizing key features of large amounts of qualitative data, using a principled approach 7Not tied to a particular level of interpretation and can be used in a wide variety of fields and disciplines (based, in part, on Braun and Clarke, 2006, pp. 96–7) 7©2011 John Wiley & Sons Ltd.

8. Disadvantages of thematic coding analysis 1The flexibility of the method means that the potential range of things that can be said about your data is broad, which can be inhibiting 2It is frequently limited to description or exploration with little interpretation 3It is not uncommon to find little information about details of the procedure 4Compared to ‘branded’ forms of analysis such as grounded theory it is a generic approach which currently has less kudos as an analytic method (based, in part, on Braun and Clarke, 2006, pp. 96–7) 8©2011 John Wiley & Sons Ltd.

9. What can you code? 1 Specific acts, behaviours 2Events 3Activities 4 Strategies, practices or tactics 5 States 6Meanings continued … 9©2011 John Wiley & Sons Ltd.

10. What can you code? - continued 7 Participation 8Relationships or interaction 9Conditions or constraints 10Consequences 11Settings (based on Gibbs, 2007, Table 4.1. pp. 47–8) 10©2011 John Wiley & Sons Ltd.

18. ISRAEL SALGADO 18 years old (1987) Not married ISRAEL SALGADO 28 years old (1997) Married, 4 children This photo was taken 10 years later, from the same spot in front of Israel’s house, in the colonia Bosques del Pedregal. It is typical of the upgrading process in irregular settlements. Upgrading of housing unit, Ajusco Medio, Mexico City

19. Example of a thematic network 19©2011 John Wiley & Sons Ltd. Source: Goldbart and Marshall, 2004

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22. Tactics to ‘generate meaning’ 1Noting patterns, themes and trends 2Seeing plausibility 3Clustering 4Making metaphors 5Counting 6Making contrasts and comparisons 7Partitioning variables continued … 22©2011 John Wiley & Sons Ltd.

23. Tactics to ‘generate meaning’ - continued 8Subsuming particulars into the general 9Factoring 10Noting relations between variables 11Finding intervening variables 12Building a logical chain of evidence 13Making conceptual/theoretical coherence based on Miles and Huberman (1994, pp. 245–6) 23©2011 John Wiley & Sons Ltd.

24. Using tables for comparative analysis Time-ordered tables where the columns are arranged in time sequence - includes event listing Role-ordered tables where the rows represent data from sets of individuals occupying different roles Conceptually clustered tables where the columns are arranged to being together items ‘belonging together’ (e.g. relating to same theme) Effects tables displaying data on outcomes Issues tables where the columns concern issues and what happens in connection with them 24©2011 John Wiley & Sons Ltd.

25. Using networks to understand patterns and relationships Types include: Context charts Event flow networks Activity records Flow charts Conceptually ordered tree diagrams Cognitive maps Causal networks 25©2011 John Wiley & Sons Ltd.

26. Assessing the quality of qualitative data analysis Assessing data quality 1 Checking for representativeness 2 Checking for researcher effect 3Triangulation 4Weighting the evidence continued … 26©2011 John Wiley & Sons Ltd.

27. Assessing the quality of qualitative data analysis - continued Testing patterns 5 Checking the meaning of outliers 6 Using extreme cases 7 Following up surprises 8 Looking for negative evidence continued … 27©2011 John Wiley & Sons Ltd.

28. Assessing the quality of qualitative data analysis - continued Testing explanations 9 Making if-then test 10 Ruling out spurious relationships 11 Replicating a finding 12 Checking out rival explanations 13 Getting feedback from informants (summarized from Miles and Huberman, 1994, p. 262–77) 28©2011 John Wiley & Sons Ltd.

29. Data analysis in multi-strategy designs 1 Data reduction. Involves summarizing both quantitative and qualitative data 2Data display. Using tables, graphs, etc. with quantitative data and matrices, charts, networks, etc. with qualitative data 3Data transformation. ‘Qualitizing’ quantitative data and/or ‘quantizing’ qualitative data 4Data correlation. Correlating quantitative data with qualitized data continued … 29©2011 John Wiley & Sons Ltd.

30. Data analysis in multi-strategy designs - continued 5Data consolidation. Combining both data types to create new variables or data sets. 6Data comparison. Comparing data from different data sources. 7Data integration. Integrating all data into a coherent whole, or separate quantitative and qualitative coherent wholes Based on Onwuegbuzie and Teddlie (2003, p. 375) 30©2011 John Wiley & Sons Ltd.

31. Strategies for integrating quantitative and qualitative data through analysis Using results from analysis of one form of data in approaching the analysis of another form of data Synthesis of data generated from a variety of sources, for further joint interpretation Comparison of coded or thematic qualitative data across groups defined by categorical or scaled variables Pattern analysis using matrices continued … 31©2011 John Wiley & Sons Ltd.

32. Strategies for integrating quantitative and qualitative data through analysis - continued Conversion of qualitative to quantitative coding to allow for statistical analysis. Conversion of quantitative data into narrative form Inherently mixed data analysis, where a single source gives rise to both qualitative and quantitative information Iterative analyses involving multiple, sequenced phases where the conduct of each phase arises out of or draws on the analysis of the preceding phase. (based on Bazeley, 2009, p. 205 ) 32©2011 John Wiley & Sons Ltd.