Qualitative Data Analysis

1
Qualitative Data Analysis

• Chapter 13

2
Introduction

• The difference between qualitative and
  quantitative data analysis is that quantitative
  data analysis invariably occurs after the data
  has been collected
• Grounded theory is by far the most widely used
  framework for analyzing qualitative data

3
Grounded Theory

• Considerable controversy as to what grounded
  theory entails (Charmaz, 2000)
• Recently grounded theory is defined as theory
  derived from systematically gathered data,
  arising through the research process (Strauss and
  Corbin, 1998)

4

• Two central features of grounded theory are
• development of theory out of data
• iterative approach meaning that data collection
  and analysis proceed in tandem, repeatedly
  referring back to each other

5
Tools of Grounded Theory

• Coding
• data is broken down into components parts and
  given names
• Theoretical saturation
• reaching a point at which there is no more point
  in reviewing old or collecting new data to see
  how they fit with concepts or categories

6

• Constant comparison
• process of maintaining a close connection between
  data and conceptualization, so that the
  correspondence between concepts and categories
  with their indicators is not lost

7
Outcomes of Grounded Theory

• Concepts
• Category, categories
• Properties
• Hypotheses
• Theory
• Substantive
• Formal

8
Coding in Grounded Theory

• Strauss and Corbin outline three types of coding
• open coding
• axial coding
• selective coding

9
Criticisms of Grounded Theory

• Some suggest claims of using grounded theory are
  unsubstantiated (Charmaz, 2000)
• Some question whether researchers can fully
  suspend awareness of existing relevant theories
  or concepts until the stage of analysis when
  theories emerge

10

• Practical difficulties with grounded theory such
  as the time it takes to transcribe recorded
  interviews
• Doubtful whether grounded theory really results
  in theory

11
Coding Steps and Considerations

• Code as soon as possible after the data are
  collected
• Read through initial set of transcripts, field
  notes, documents, etc.
• Do it again!
• Do not worry about generating too many codes

12

• Review the codes, possibly in relation to
  transcripts
• Consider more general theoretical ideas in
  relation to codes and data
• Keep coding in perspective

13
Problems with Coding

• Possibility of losing what is said
• Results in a fragmentation of data, so that the
  narrative flow of what people say is lost (Coffey
  and Atkinson, 1996)

14
Narrative Analysis

• Covers a wide variety of approaches concerned
  with the search for and analysis of stories that
  people employ to understand their lives and the
  world around them
• Particularly prominent in connection with the
  life history or biographical approach

15

• Riessman (2004) distinguished four models of
  narrative analysis
• thematic analysis
• structural analysis
• interactional analysis
• performative analysis