Qualitative Data
Analysis: An Introduction
Carol Grbich
Chapter 6. Grounded
Theory
Grounded Theory
 Use for exploring relationships or observing micro
interaction
 Use where little previous knowledge exists
 Developed by Barney Glaser and Anselm Straus who
wanted to develop theory from data in the real world
Current versions include:
Barney Glaser’s version
Anselm Strauss’ version
 Kathy Charmez’ constructivist Grounded theory version
 Postmodern and conjoint orientations
Grounded theory assumptions
 Assumptions underpinning GT- Symbolic Interactionism
presumes reality is constructed and social processes can
be created and changed by interactions among people,
 ‘Meaning’ is constructed through symbols, signs and
language, and our ability to take the position of others
through the ‘I’ (the uninhibited self) and the ‘me’ (the
societal controls reflected in the attitudes, values and
behaviours of significant others).
 The focus in grounded theory is - the empirical, social
world ‘out there’ viewed as comprising many different
layers, and public and private views.
Differences between Strauss & Glaser
Glaser
Style
Question
critiquing
Strauss
discovery
problem + variations
Process
emergent directions
Lit. review
ongoing from 1st
verification
dimensionalising &
coding & hypothesis testing
when categories emerge - if desired
Category identification
Coding
Open coding
Axial coding
constant comparison
words, lines, sections
unnecessary
Selective coding core variables only
categories
Theory
theory generation
3 levels of data fracturing
words, lines paragraphs
meticulous procedure
core categories to other
theory verification
Strauss’ grounded theory
 Dimensionalising and sub -dimensionalising
(research question)
 Open coding (data opening up through
questioning)
 Memos (detailed summation of observation and
data linking to concepts and literature)
 Axial coding (grouping of categorical data)
 Selective coding (linking of core categories with
memos and literature
 Integration (putting it all together)
Glaser’s Grounded theory
 No data fracturing
 Constant comparison of incident to to
incident and to emerging concepts
 Use of open coding, theoretical sampling
and constant comparison techniques
 Group emergent categories, generate
connections and link to literature
Theoretical sensitivity
 A process of becoming steeped in the literature
using the ‘variables’ emerging from the data and
seeking conceptual and theoretical connections
to provide interpretations in the generation of
new theory (Glaser)
 Linking of data and theory more for verification
rather than generation of new ideas but being
careful not to let existing views bias your
perceptions. (Strauss)
Development of formal theory
 Identify the core category to be developed
 Open code and write memos of an example of the data in which this category
occurs
 Theoretically sample in a range of different areas
 Continue until a wide range of sources have been covered Strauss (1987:2412)
Criteria for evaluating substantive / formal theory
 Fit – the link between the theory and the arena where it will be used to provide
insight needs to be clear
 Understandability – will the theory be meaningful to those who don’t work in
the area from which the data has been collected?
 Generaliseability – the theory needs to be meaningful in a large range of areas
 Control – does the theory empower users within the field with knowledge to
improve their situation? (adapted from Glaser and Strauss, 1967:237)
Criticisms of Grounded Theory
 A focus on a quasi-objective centred researcher
 Existing theories cannot be ignored by avoiding a
literature review, the researcher invariably comes to
the research topic bowed under the weight of
intellectual baggage from his/her own discipline.
 There is a focus on a complex method and confusing
and overlapping terminology rather than data.
 Poorly integrated theoretical explanations tend to be
Charmez’s Constructivist Grounded Theory :
differences
Researcher and researched
 She challenges the previously ‘objective’ distant nature of the
relationship between researcher and participants
 She refocusses on researchers and their critical reflective role in the
recognition and management of their biases
Data accountability
 Immersion in and transposing raw data into memos is one suggested
way of keeping close and accountable to data (maintaining participants
voices)
 Using non-scientific writing styles closer to the literary options
available in postmodern approaches forefronts voices of the researched