QUALITATIVE RESEARCH METHODS – QUALITATIVE DATA ANALYSIS APPROACHES
1. Grounded theory (31/10)
1.1. Introduction
Grounded Theory (GT):
- It’s highly appropriate if you want to move beyond description and instead build a more thorough
explanation or understanding of a particular phenomenon.
- It requires an open mind regarding the focus of your research and the kinds of data you will sample
(as these are expected to change as you progress with the analysis of the data).
1.2. Key features
Grounded theory has some important publications:
In 1967 In 1990 In 2006
It was first introduced by Glaser There is an influential book by There is another influential
and Strauss in their textbook. Strauss and Corbin. approach by Charmaz.
Inclusion of term “GT” in publications over time:
In 1992 In 2020
Less than 200 More than 1800
1.3. Historical developments
GT publications:
- The majority can be found in the disciplines of nursing, health sciences and psychology (because
Glaser and Strauss applied to it).
- These are also in the fields of educational sciences.
- These are also (to a lesser extent) in the disciplines of sociology, political sciences, communication
sciences, and anthropology.
Initially, GT was developed as a backlash against deductive, top-down quantitative method with a deduction
from grand theories to middle-range theories verified by statistical techniques (their hypothesis was testing
based on existing theories).
Glaser and Strauss (1967):
- They argued that theory could also be developed bottom-up (= inductively, an inductive theory)
instead of testing hypotheses based on existing theory.
- They argued that it was applicable to both quantitative and qualitative data, but mostly advanced
to analyze qualitative data (at a time when such analysis was largely considered un-scientific by
the sociological research community).
For many years, GT:
- It has been various changes that have affected the procedures when carrying out data analyses.
- It was not applied appropriately by researchers for several reasons:
o There are different versions of GT and no clear methodology.
o The conceptualizations of GT are related to the historical context in which these were
situated.
1
, 1.4. Generic Inductive Qualitative Model (GIQM)
Hood makes the distinction between the Generic Inductive Qualitative Model (GIQM) and GT.
GIQM follows several principles that are often seen as characteristics of qualitative data analysis in general
(but which don’t necessarily correspond to what GT stands for).
>> If you do not apply GT entirely (ex.: in your thesis), don’t sell it as actual GT (apply GIQM or other forms
of qualitative data analysis).
1.4.1. Principes
GIQM is a more pragmatic approach of qualitative data analysis:
- It focuses on research questions that:
o Emphasize the development of a deep understanding or explanations.
o Explore new hypotheses rather than testing existing ones.
o Emphasize on the interpretation of meaning.
o Emphasize rich and contextual description.
o Have a focus on the process (over time).
o Are based on literature.
- It has a research design that is continuously adapted as analysis and data collection (= an iterative
process), which allows constantly adjust the design.
- It focuses on interpretation of text: GIQM places high value on the interpretation of textual data
(unlike quantitative methods that prioritize statistical results).
- It focuses on processes rather than explaining variance (to what extent and why something
happens).
- It applies a three-step coding process to analyze data: this process enhances the level of
abstraction in the analysis (allowing for a nuanced understanding of complex phenomena):
STEP 1 STEP 2 STEP 3
Identify codes Integrate codes Apply codes
List the codes that emerge from Group and connect these codes Use the integrated codes to
the data. to create themes. abstract and interpret data
more deeply.
- It uses writing (memo-type synthesis) as a key tool in analyzing/interpretating data: by
documenting thoughts and observations, researchers refine their analysis, organize ideas, and
build coherent interpretations.
- It selects samples/texts/cases/contexts based on their theoretical relevance: these are selected
based on their relevance to the theoretical framework or research QST rather than for statistical
representation.
- It uses (reasonably) raw data when presenting the outcome of data analysis (to provide
transparency). Ex.: ITV quotes, photos, visual representations (like coding trees or thematic maps).
- It presents findings and theoretical relevance together in an integrated way (and not separately,
which is more common in quantitative research): there is not different sections.
- It claims that data collection stops when new cases no longer add new information.
- It claims that theoretical sample draw is predetermined and unchanged throughout the study
(chosen based on theory and expected theoretical relevance).
1.4.2. Differences between GIQM and GT
2
, GIQM GT
Sample if fixed at the beginning of the study and Sample changes throughout the study.
remains unchanged.
Data analysis often stops when analysis of There is a theoretical saturation.
additional data doesn’t yield new insights. Ex.: you
feel like “you have heard it all before”.
1.5. Pragmatic, orthodox, and “anything can” approaches of/to qualitative data analysis
In qualitative data analysis, there are several approaches that researchers can choose from (each with its
own level of structure and flexibility):
Pragmatic approach Orthodox approach(es) “Anything can” (or “whatever
works”) approach
It focuses on the - It gives more guidance: it follows - It emphasizes flexibility: any
using of methods clear structured steps for data method that achieves results is
that best serve the collection, analysis, interpretation. valid.
research goals rather - It includes predefined - It often overlaps with a more
than adhering strictly indicators/criteria to evaluate the pragmatic approach because it
to a procedure. quality of the analysis (= indicators gives less guidance to the novice
of quality) to ensure that the researcher.
results are reliable. - There is no clear step.
- It’s a more classical way.
>> There is nothing wrong with a more pragmatic approach.
>> Central to any approach: high-quality analyzes (the central goal in qualitative research).
High-quality is defined by:
- The credibility of the findings: it’s achieved through rigorous methods, transparency in the process
and valid techniques. Ex.: triangulation, member checking, peer debriefing.
- The theoretical relevance of the findings: the findings contribute to the understanding of the topic
and the related theoretical framework.
1.6. Doing GT step by step
1.6.1. Three main and other features
Three features that are shared by different approaches to GT:
- It employs a form of theoretical sampling that is often not applied in GIQM-inspired research:
o The sampling (ex.: who/documents you will ITV/observe/analyze) is not fixed but dynamic:
• It can’t be determined in advance but must change as a function of the theory
developed.
• It’s informed by theory. //GIQM
• It evolves with the research: researchers select participants/data sources based
on emerging patterns/themes that need further exploration.
o It has several steps as long as necessary to develop a theory (ex.: parenting styles; research
on different mother’s and father’s views on being a good parent):
• STEP 1: you select a more homogeneous sample to develop a basic theory/
understanding/explanations of the phenomena. Ex.: you start by interviewing 4
fathers and 4 mothers.
• STEP 2: once you have developed a basic theory, you select a particular
phenomenon as the focus of your research.
3
, • STEP 3: you develop a theoretical sample in which you select cases that allow you
to further develop your theory in relation to that phenomenon. Ex.: it turns out to
be interesting to interview other categories of respondents as well and so you add
them to the sample (ex.: grandparents).
o It’s important to only select data that is relevant for research (= data that contribute to
develop the emerging theory).
- It employs a constant comparative method:
Constant comparative approach in QDA Grounded Theory (GT) approach
- It involves analyzing data by continuously - Comparisons are open-ended and guided by
comparing new data (e.g., interviews, field the emerging theory.
notes) with previously analyzed data. - It doesn’t begin with predefined categories
- It focuses on refining understanding of (ex.: parenting styles: comparing mothers with
predefined categories (e.g., fathers vs. mothers or fathers with fathers); instead, data
mothers in parenting styles). is compared as a whole initially.
- Categories and themes develop inductively
from the data.
Ex.: parenting styles:
- STEP 1: you compare various ITV or field notes without limiting yourself to predefined categories.
Ex.: women with women and men with men.
- STEP 2: as patterns emerge, you might find that “family-work balance” is a recurring theme across
the data, regardless of gender or parental role.
- STEP 3: these themes may shift the focus of analysis and further comparisons.
- STEP 4: sampling and comparisons then prioritize understanding these emergent issues, refining
theoretical insights.
- It reaches the theoretical saturation:
Constant comparative approach in QDA Grounded Theory (GT) approach
It stops analyzing data when analysis of data You stop collecting/analyzing data when you feel
doesn’t reveal new insights. that you have developed a comprehensive
understanding/explanation of a particular
phenomenon. Ex.: parenting styles: if you still
have unanswered questions about “work-family
balance”, you can investigate using additional
data until you have built up a complete
statement. = the theoretical saturation
Three other features of GT on which there is more discussion between GT researchers:
- What does it mean to develop a “theory”:
o GT leads to innovative theories rather than testing/confirming existing theories.
o As is evident from the name, a key purpose of GT is to build a theory BUT there are
differences among authors about what they consider as “theory” or a valid end product of
a GT analysis; there are differences between two paradigms:
A post-positivist approach Constructivist approach
Straus and Corbin (1998) Charmaz
- For them, the goal of GT is to develop - She rejects the idea that you should aim to
explanatory models that help us to develop explanations of phenomena that are
understand how reality is. as accurate as possible.
- For them, a theory is a set of well-developed - She starts with the premise that there are
concepts, related by statements of multiple realities.
relationship, that together form an integrated
4
1. Grounded theory (31/10)
1.1. Introduction
Grounded Theory (GT):
- It’s highly appropriate if you want to move beyond description and instead build a more thorough
explanation or understanding of a particular phenomenon.
- It requires an open mind regarding the focus of your research and the kinds of data you will sample
(as these are expected to change as you progress with the analysis of the data).
1.2. Key features
Grounded theory has some important publications:
In 1967 In 1990 In 2006
It was first introduced by Glaser There is an influential book by There is another influential
and Strauss in their textbook. Strauss and Corbin. approach by Charmaz.
Inclusion of term “GT” in publications over time:
In 1992 In 2020
Less than 200 More than 1800
1.3. Historical developments
GT publications:
- The majority can be found in the disciplines of nursing, health sciences and psychology (because
Glaser and Strauss applied to it).
- These are also in the fields of educational sciences.
- These are also (to a lesser extent) in the disciplines of sociology, political sciences, communication
sciences, and anthropology.
Initially, GT was developed as a backlash against deductive, top-down quantitative method with a deduction
from grand theories to middle-range theories verified by statistical techniques (their hypothesis was testing
based on existing theories).
Glaser and Strauss (1967):
- They argued that theory could also be developed bottom-up (= inductively, an inductive theory)
instead of testing hypotheses based on existing theory.
- They argued that it was applicable to both quantitative and qualitative data, but mostly advanced
to analyze qualitative data (at a time when such analysis was largely considered un-scientific by
the sociological research community).
For many years, GT:
- It has been various changes that have affected the procedures when carrying out data analyses.
- It was not applied appropriately by researchers for several reasons:
o There are different versions of GT and no clear methodology.
o The conceptualizations of GT are related to the historical context in which these were
situated.
1
, 1.4. Generic Inductive Qualitative Model (GIQM)
Hood makes the distinction between the Generic Inductive Qualitative Model (GIQM) and GT.
GIQM follows several principles that are often seen as characteristics of qualitative data analysis in general
(but which don’t necessarily correspond to what GT stands for).
>> If you do not apply GT entirely (ex.: in your thesis), don’t sell it as actual GT (apply GIQM or other forms
of qualitative data analysis).
1.4.1. Principes
GIQM is a more pragmatic approach of qualitative data analysis:
- It focuses on research questions that:
o Emphasize the development of a deep understanding or explanations.
o Explore new hypotheses rather than testing existing ones.
o Emphasize on the interpretation of meaning.
o Emphasize rich and contextual description.
o Have a focus on the process (over time).
o Are based on literature.
- It has a research design that is continuously adapted as analysis and data collection (= an iterative
process), which allows constantly adjust the design.
- It focuses on interpretation of text: GIQM places high value on the interpretation of textual data
(unlike quantitative methods that prioritize statistical results).
- It focuses on processes rather than explaining variance (to what extent and why something
happens).
- It applies a three-step coding process to analyze data: this process enhances the level of
abstraction in the analysis (allowing for a nuanced understanding of complex phenomena):
STEP 1 STEP 2 STEP 3
Identify codes Integrate codes Apply codes
List the codes that emerge from Group and connect these codes Use the integrated codes to
the data. to create themes. abstract and interpret data
more deeply.
- It uses writing (memo-type synthesis) as a key tool in analyzing/interpretating data: by
documenting thoughts and observations, researchers refine their analysis, organize ideas, and
build coherent interpretations.
- It selects samples/texts/cases/contexts based on their theoretical relevance: these are selected
based on their relevance to the theoretical framework or research QST rather than for statistical
representation.
- It uses (reasonably) raw data when presenting the outcome of data analysis (to provide
transparency). Ex.: ITV quotes, photos, visual representations (like coding trees or thematic maps).
- It presents findings and theoretical relevance together in an integrated way (and not separately,
which is more common in quantitative research): there is not different sections.
- It claims that data collection stops when new cases no longer add new information.
- It claims that theoretical sample draw is predetermined and unchanged throughout the study
(chosen based on theory and expected theoretical relevance).
1.4.2. Differences between GIQM and GT
2
, GIQM GT
Sample if fixed at the beginning of the study and Sample changes throughout the study.
remains unchanged.
Data analysis often stops when analysis of There is a theoretical saturation.
additional data doesn’t yield new insights. Ex.: you
feel like “you have heard it all before”.
1.5. Pragmatic, orthodox, and “anything can” approaches of/to qualitative data analysis
In qualitative data analysis, there are several approaches that researchers can choose from (each with its
own level of structure and flexibility):
Pragmatic approach Orthodox approach(es) “Anything can” (or “whatever
works”) approach
It focuses on the - It gives more guidance: it follows - It emphasizes flexibility: any
using of methods clear structured steps for data method that achieves results is
that best serve the collection, analysis, interpretation. valid.
research goals rather - It includes predefined - It often overlaps with a more
than adhering strictly indicators/criteria to evaluate the pragmatic approach because it
to a procedure. quality of the analysis (= indicators gives less guidance to the novice
of quality) to ensure that the researcher.
results are reliable. - There is no clear step.
- It’s a more classical way.
>> There is nothing wrong with a more pragmatic approach.
>> Central to any approach: high-quality analyzes (the central goal in qualitative research).
High-quality is defined by:
- The credibility of the findings: it’s achieved through rigorous methods, transparency in the process
and valid techniques. Ex.: triangulation, member checking, peer debriefing.
- The theoretical relevance of the findings: the findings contribute to the understanding of the topic
and the related theoretical framework.
1.6. Doing GT step by step
1.6.1. Three main and other features
Three features that are shared by different approaches to GT:
- It employs a form of theoretical sampling that is often not applied in GIQM-inspired research:
o The sampling (ex.: who/documents you will ITV/observe/analyze) is not fixed but dynamic:
• It can’t be determined in advance but must change as a function of the theory
developed.
• It’s informed by theory. //GIQM
• It evolves with the research: researchers select participants/data sources based
on emerging patterns/themes that need further exploration.
o It has several steps as long as necessary to develop a theory (ex.: parenting styles; research
on different mother’s and father’s views on being a good parent):
• STEP 1: you select a more homogeneous sample to develop a basic theory/
understanding/explanations of the phenomena. Ex.: you start by interviewing 4
fathers and 4 mothers.
• STEP 2: once you have developed a basic theory, you select a particular
phenomenon as the focus of your research.
3
, • STEP 3: you develop a theoretical sample in which you select cases that allow you
to further develop your theory in relation to that phenomenon. Ex.: it turns out to
be interesting to interview other categories of respondents as well and so you add
them to the sample (ex.: grandparents).
o It’s important to only select data that is relevant for research (= data that contribute to
develop the emerging theory).
- It employs a constant comparative method:
Constant comparative approach in QDA Grounded Theory (GT) approach
- It involves analyzing data by continuously - Comparisons are open-ended and guided by
comparing new data (e.g., interviews, field the emerging theory.
notes) with previously analyzed data. - It doesn’t begin with predefined categories
- It focuses on refining understanding of (ex.: parenting styles: comparing mothers with
predefined categories (e.g., fathers vs. mothers or fathers with fathers); instead, data
mothers in parenting styles). is compared as a whole initially.
- Categories and themes develop inductively
from the data.
Ex.: parenting styles:
- STEP 1: you compare various ITV or field notes without limiting yourself to predefined categories.
Ex.: women with women and men with men.
- STEP 2: as patterns emerge, you might find that “family-work balance” is a recurring theme across
the data, regardless of gender or parental role.
- STEP 3: these themes may shift the focus of analysis and further comparisons.
- STEP 4: sampling and comparisons then prioritize understanding these emergent issues, refining
theoretical insights.
- It reaches the theoretical saturation:
Constant comparative approach in QDA Grounded Theory (GT) approach
It stops analyzing data when analysis of data You stop collecting/analyzing data when you feel
doesn’t reveal new insights. that you have developed a comprehensive
understanding/explanation of a particular
phenomenon. Ex.: parenting styles: if you still
have unanswered questions about “work-family
balance”, you can investigate using additional
data until you have built up a complete
statement. = the theoretical saturation
Three other features of GT on which there is more discussion between GT researchers:
- What does it mean to develop a “theory”:
o GT leads to innovative theories rather than testing/confirming existing theories.
o As is evident from the name, a key purpose of GT is to build a theory BUT there are
differences among authors about what they consider as “theory” or a valid end product of
a GT analysis; there are differences between two paradigms:
A post-positivist approach Constructivist approach
Straus and Corbin (1998) Charmaz
- For them, the goal of GT is to develop - She rejects the idea that you should aim to
explanatory models that help us to develop explanations of phenomena that are
understand how reality is. as accurate as possible.
- For them, a theory is a set of well-developed - She starts with the premise that there are
concepts, related by statements of multiple realities.
relationship, that together form an integrated
4
