This document discusses qualitative research methods and mixing methods approaches. It begins by defining different qualitative research types like case studies, grounded theory, phenomenology, and ethnography. It then discusses multi-strategy research, noting both advantages like breaking down qual-quant divides, but also difficulties integrating methods from different epistemological perspectives. The document outlines arguments for and against mixing methods and different versions of the debate. It also discusses triangulation strategies and other mixed methods approaches like sequential or concurrent designs.

1. Qualitative Research Methods
Thinking about ‘triangulation’ & other issues
of mixing methods.
By Dr.Ammara Khakwani

2. Learning Objectives
By the end of this course, you should be able to:
1. Critically discuss the arguments for & against multi-
strategy research
2. Appreciate the range of possibilities in engaging in
multi-strategy research, including triangulation
3. Understand what is meant by ‘mixing methods in a
qualitatively driven way’ as outlined by Mason (2006)
4. Critically reflect on the appropriateness of multi-
strategy research for your own research interests

3. Contents
• Part 1 Theory: Qualitative research, Multi-level strategy
and triangulation
• Part 2 Types of triangulation + Activity
• Part 3 Practical example

4. Part 1: Theory
Types of qualitative research
Case study Attempts to shed light on a phenomena by
studying indepth a single case example of the
phenomena. The case can be an individual
person, an event, a group, or an institution.
Grounded theory Theory is developed inductively from a corpus
of data acquired by a participant-observer.
Phenomenology Describes the structures of experience as they
present themselves to consciousness, without
recourse to theory, deduction, or assumptions
from other disciplines
Ethnography Focuses on the sociology of meaning through
close field observation of sociocultural
phenomena. Typically, the ethnographer
focuses on a community.
Historical Systematic collection and objective evaluation
of data related to past occurrences in order to
test hypotheses concerning causes, effects, or
trends of these events that may help to explain
present events and anticipate future events.
(Gay, 1996)

5. Multi-strategy research
•Refers to research that combines
qualitative & quantitative research
•On the surface, this can be seen as a
straightforward way of breaking down the
qual-quant divide
•But if we dig deeper, this approach is not
without difficulties

6. Make a list:
• What are some of the advantages?
• What are some of the difficulties?

7. The Argument Against Multi-strategy
Research (I)
The embedded methods argument:
 Research methods carry epistemological and
ontological commitments
 Thus multi-strategy research is not feasible or
even desirable
Why?
 Integrating research strategies could lead to
danger of ignoring assumptions underlying
research methods
 Could result in transforming “qualitative inquiry
into a procedural variation of quantitative inquiry”
(Smith & Heshusius, 1986: 8)

8. The Argument Against Multi-strategy
Research (II)
• The paradigm argument:
 Quantitative and qualitative research are
separate, incommensurable paradigms
 Thus even when combined they are
incompatible: the integration is only at a
superficial level and within a single paradigm

9. Your view:
• Do you see data as just data?
• Your reflection on this shapes how you
engage in the multi-strategy research
debate

10. Two Versions of the Debate About
Quantitative and Qualitative Research
• An epistemological version:
 as in the embedded methods argument and the
paradigm argument, multi-strategy research is not possible
•A technical version:
 Emphasises the strengths of data collection and data
analysis techniques associated with quantitative and
qualitative research and sees these as capable of being
fused
 Research methods are perceived as autonomous and
compatible

11. Your view:
• Think about ways in which multi-strategy
research can take place
• In particular, think about how and why
• The ‘why’ question compels us to provide a
rationale for the choices we make if and when
we choose to combine methods

12. Subjectivist
Projection of human imagination
Social construction
Contextual field of information
Concrete process
Concrete structure
Objectivist
Different assumptions about reality from Morgan and Smircich (1980).
Quantitative vs Qualititive
Researcher is independent vs Researcher is involved
Large samples vs Small samples
Testing theories vs Generating theories
Experimental design vs Fieldwork methods
Verification vs Falsification
The choices of research design (Hassard, 2002).

13. Theory
Empirical
Generalization
Deduction, induction and Retroduction representation of how deduction, induction and
Retroduction work through the empirics and theory (Alvesson and Skoldberg, 1994).
Empirical
Deduction Induction Retroduction
Deduction Logical inferences from major and minor
premises
Formally correct but sometimes
empirically flawed- it depends on the
correctness of premises
Induction The ability to form probability statements when
all conditions being equal the higher past
frequency the higher the probability
Inductive thinking is susceptible to
habit and expectation
Abduction The act of seeing something anew to connect a
case with an unexpected rule related to vague
common sense
Abductive reasoning is Perceptual
judgments and their clarity is
questionable
Retroduction Aims to specify the necessary and sufficient
causes and conditions to be produced or
reproduced, for the phenomenon to come into
existence.
The four types of scientific abstraction – logical reasoning (as in Bertilsson, 2004).
Ontology and
epistemology

14. Triangulation – popular strategy for
mixing methods
• It is based on the assumption that “any bias
inherent in particular data sources, investigator,
and method would be neutralised when used in
conjunction with other data sources,
investigators and methods”
(Creswell, 1994: 174)
• It assumes that data from different methods will
corroborate one another, where the choice of
methods is intended to investigate a single social
phenomenon from different vantage points
(Denzin,1970; Brannen,2005)

15. Combining methods & data: many possible outcomes
“Data collected from different methods cannot be simply added
together to produce a unitary or rounded reality” (Brannen 2005: 176)
 Triangulation (see corroboration) is just one of many possible
outcomes
1.Corroboration: The ‘same result’ are derived from both
qualitative and quantitative methods
2.Elaboration: The qualitative data analysis exemplifies how the
quantitative findings apply in particular cases.
3.Complementarity: The qualitative and quantitative results differ
but together they generate insights.
4.Contradiction: Where qualitative data and quantitative findings
conflict.
(Morgan, 1998, cited in Bryman, 2001; Hammersley, 1996)

16. Part 2: Types of Triangulation –strategy
for mixing methods
• It is based on the assumption that “any bias inherent in
particular data sources, investigator, and method would be
neutralised when used in conjunction with other data
sources, investigators and methods”
(Creswell, 1994: 174)
• It assumes that data from different methods will
corroborate one another, where the choice of methods is
intended to investigate a single social phenomenon from
different vantage points
(Denzin, 1970; Brannen, 2005)

17. Types of Triangulation
• Methods Triangulation
One researcher using two or more research techniques (within and between QUAN-
QUAL techniques);
Two or more researchers using the same research technique;
Two or more researchers using two or more research techniques.
• Theoretical Triangulation
Looking at the research situation from different theoretical perspectives.
• Data Triangulation
Combining qualitative and quantitative data within the same method.
The types of data these three methods generate are field notes, audio (and
sometimes video) recordings, and transcripts.

18. Mixed Methods Strategies
• What is the implementation sequence of the QUAN and
QUAL data collection in the proposed study?
• What priority will be given to the QUAN and QUAL data
collection and analysis?
• At what stage in the research project will the QUAN and
QUAL data and findings be integrated?

19. 1. Implementation
• Sequential
The researcher collects both the QUAN and QUAL data in phases
• Concurrent
The researcher collects both the QUAN and QUAL data at the same time

20. 2. Priority
• Equal priority
Same weight is given to QUAN and QUAL
• Dominant and less-dominant priority
Priority for either QUAN or QUAL

21. 3. Integration
• Integration of QUAN and QUAL data might occur at several
stages in the process of research:
Data collection
Data analysis
Interpretation
Or combination of places

22. Alternative Strategies and Visual Models
• Sequential Explanatory Strategy
Use QUAL results to assist in explaining and interpreting the findings of a primarily
QUAN study.
Especially useful when unexpected results arise from QUAN study.

23. Alternative Strategies and Visual Models
(cont.)
• Sequential Explanatory Design
Qual
QUAN
Data
Collection
QUAN
Data
Analysis
qual
Data
Collection
qual
Data
Analysis
Interpretation
of Entire
Analysis
QUAN
Use QUAN data and results in the interpretation of QUAL findings.
Focus of this model is on exploring a phenomenon.

24. Alternative Strategies and Visual Models
(cont.)
• Sequential Exploratory Design
QUAL quan
QUAL
Data
Collection
QUAL
Data
Analysis
quan
Data
Collection
quan
Data
Analysis
Interpretation
of Entire
Analysis

25. Alternative Strategies and Visual Models
(cont.)
• Concurrent Triangulation Strategy
QUAN QUAL
QUAN
Data
Collection
QUAN
Data
Analysis
QUAL
Data
Collection
QUAL
Data
AnalysisData results compared
Selected as a model when the researcher uses two different methods in an attempt to
confirm, cross-validate, or corroborate findings within a single study.

26. Alternative Strategies and Visual Models
(cont.)
• Concurrent Nested Strategy
Qual Quan
QUAN QUAL
Analysis of Findings Analysis of Findings
Often used to gain broader perspectives as a result of using the different methods
May be employed to study different groups or levels

27. Other qualitative strategies
• Multiple case studies, quantification of qualitative data
• Within qualitative methods triangulation
1. Participant observation is appropriate for collecting data on
naturally occurring behaviours in their usual contexts.
2. In-depth interviews are optimal for collecting data on
individuals’ personal histories, perspectives, and
experiences, particularly when sensitive topics are being
explored.
3. Focus groups are effective in eliciting data on the cultural
norms of a group and in generating broad overviews of issues
of concern to the cultural groups or subgroups represented.

28. Activity : think of your own research
• What is my ontology
• What is my epistemology
• What are my methods
• What type of data am I going to use
• What kind of answer do I look for: what, how or why

29. Part 3 Example: qualitative multiple case studies
using Critical Realism
• My Research
Question: Why and
how projects succeed
or otherwise
• Why and how needs in
depth rich data
• Qualitative rich data
usually are collected
through qualitative
interviews-focus
groups etc and
analysed within case
studies
Problem: Generalizability is low in case studies
Problem: I needed to generalize the causes of an extended
observed phenomenon in quantitative research

30. Choices
• Wouldn’t it be good
to generalize from
many case studies
like as if from a
survey
Finding patterns of
behaviour and
explanation through
many case studies
strengthen the
argument placed by
evidence
Problem: Finding patterns in case studies? Horrific !
Blending ontologies and epistemologies – very tricky
indeed !

31. Research design
Research Question: What is the effect of Policy on Project Management?
Method: Multiple, explanatory comparative cross cases
Instrumentation: Human In-depth, Semi-structured interviews
Purpose: Building model Understand social interpretations of a phenomenon and
built a model to represent it.
Data: Subjective Data are perceptions of the people in the environment.
Orientation: Causality Find how the issues involved interact.
Focus: Holistic A total or complete picture is sought.
Reality: Dynamic Reality changes with changes in people’s perceptions.
Viewpoint: Insider Reality is what people perceive it to be
Results: Valid The focus is on design and procedures to gain "real,"
"rich," and "deep" data.
Analysis: Retroduction Deductively collecting inductively analyzing and
abductively concluding and theorizing

32. Normative, Descriptive and Systems theories
in Project Management
Stakeholderism vs boundary roles
Policy
Project Management
Operational
Change
Public Policy
Implementation
Strategy public sector -
Institutions
Managing projects in
change – planned vs
emergent approaches
Relationality

33. Core Ontological Assumptions Reality as a concrete process
Assumptions About Human Nature Man as an adaptor
Basic Epistemological Stance To study systems, process, change
Favored Metaphors Organism
Table 6.1: The ontological assumptions of CR (Downward, 2008:
314).
Real
Actual
Empirical
Contingent
conditions
Triggers
Observation
Experience
Intrinsic objects
Mechanisms
Events and
tendencies
Patterns
may or may not fire
may or may not
be observable
The ontology of CR
(the author from
Modell, 2005)

34. Real
Actual
Empirical
Contingent
conditions
Instruments
Observation
Experience of
participants
Policy
Mechanisms
Programme
actions and
contexts
Project
Management

35. Epistemology Basic ideas Role of theory
What is real is not given.
The world has structure
(there are levels of reality)
and emergent structures.
People’s involvement with
structures is
transformational.
Subject matter has to reflect
both its meaningfulness to
actors and their location in a
given network of
relationships and structures.
Knowledge is dualistic.
Theory is a conjecture
about the
connectedness of
events and the causal
sequences produced
by generative
mechanisms.
Nature of explanation Method of study
Something is explained if
it is allocated a place at
the end of a causal
sequence. There may be
multiple causes of a
single event, co-variation
and feedback
The aim is to produce a
good theory which
accurately identifies causal
mechanisms. The ways
these work themselves out in
given cases will be
complicated. Multiple data is
required
Ackroyd (2004: 150-
1) on the
characteristics of CR

36. 1. 17 multiple case studies
2. Could quantify results but didn’t
3. Instead I made a conceptual model based
on the common causal explanations directly
within and across embedded case studies
4. I linked the data to the literatures using the
framework of open systems

37. Mixing methods in a qualitatively driven
way…
Jennifer Mason (2006)

38. Mixing methods in a qualitative driven way
(Mason, 2006)
• Contributes to the debate of multi-strategy research by arguing
“the value of mixed-methods approaches for researching
questions about social experiences and lived realities” (Mason,
2006: 9)
• Makes a case for looking at mixed-methods as “multi-
dimensional research that transcend or even subvert the so-
called qualitative divide” (Mason, 2006: 9)
• “social experience and lived realities and multi-dimensional...
our understandings are impoverished and may be
inadequate if we view these phenomena only along a single
dimension” (Mason, 2006: 10)

39. ‘Meshing’ methods? (I)
• Mason (2006) proposes that instead of talking about
‘integrating’ methods & data, perhaps it is more useful
to describe mixing methods as ‘linking’ or ‘meshing’
processes
• “But how can this be done without sinking into a
relativist mire, where we have many different and
fragmented descriptions of social experience, but no real
explanation of anything? On the face of it, mixed-
methods approaches are trapped between the devil and
the deep blue sea”
(Mason, 2006: 20)

40. ‘Meshing’ methods? (II)
•“I think the answer lies in how we construct our
explanations and what we expect them to do.
Explanations do not have to be internally
consensual and neatly consistent to have
meaning and to have the capacity to explain.
Indeed, if the social world is multi-dimensional,
then surely our explanations need to be
likewise?” (Mason, 2006: 20)

41. ‘Meshing’ methods? (III)
Essentially, Mason (2006) argues for going
beyond divides, including qual-quant; micro-
macro; global-local, socio-cultural-individual in
order to acknowledge the multi-dimensionality
of contexts & how they intersect to shape
social experience & lived realities

42. Qualitative derived principles for mixing methods
(Mason, 2006: 21-22) (I)
• Underpinned by a qualitative constructivist approach & the aim
of understanding the how and why of social experience & lived
realities
1. A questioning, reflexive, and non-accepting approach to
research design & practice
2. Recognising the validity (legitimacy) of more than one approach
3. A flexible, creative approach

43. Qualitative derived principles for mixing methods
(Mason, 2006: 21-22) (II)
4. Celebrating richness, depth, complexity, and nuance (through
embracing a range of data types & sources, including
‘quantitative’ understandings)
5. A reflexive approach to what it is that data represent & how
they constitute knowledge
• this involves questions about the contexts/situatedness of the
social phenomena / processes being investigated & extent to
which the methods used can provide knowledge about them
• E.g. Are they to be found in people’s behaviours, practices,
imaginations, in physical or visual environments, in norms or
discourses, etc.?

44. Questions?

45. Reading
Bryman and Bell (2007): Chapter 25: Mixed methods research:
Combining quantitative and qualitative research
You might also want to look at:
Brannen, J. (2005). Mixing Methods: The Entry of Qualitative and
Quantitative Approaches into the Research Process. Int. J. Social
Research Methology, 8(3), 173-184.
Bryman, A. (2007). Barriers to Integrating Quantitative and Qualitative
Research. Journal of Mixed Methods Research, 1(1), 8-22.
Mason, J. (2006). Mixing methods in a qualitatively driven way.
Qualitative Research, 6(1), 9-25.

46. Other references
• Campbell, D.T. and Fiske, D.W. (1959): “Convergent and Discriminant
Validation by the Multitrait-Multimethod Matrix”, Psychological Bulletin,
iss.2, pp.81-105.
• Cherryholmes, C.H. (1993): “Notes on Pragmatism and Scientific
Realism”, Educational Researcher, vol.21, iss.6, pp.13-17.
• Creswell, J.W. (1994): Research Design: Qualitative & Quantitative
Approaches, (Sage Publications: U.S.A.).
• Creswell, J.W. (2003): Research Design: Qualitative, Quantitative and
Mixed Methods Approaches, 2nd ed., (Sage: U.K.).
• Datta, L. (1994): “Paradigm Wars: A Basis for Peaceful Coexistence and
Beyond”, in Reichardt, C.S. and Rallis, S.F. (eds.): The Qualitative-
Quantitative Debate: New Perspectives, pp.53-70, (Jossey-Bass: San
Francisco).

47. ...... references .......
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Inc.: London).
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Rosenstiel, L., and Wolff, S. (eds.): Handbuch Qualitative
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• Flick, U. (1992): “Triangulation Revisited: Strategy of Validation or
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• Flick, U. (1998): An Introduction to Qualitative Research, (Sage: U.S.A.).
• Silverman, D. (2000): Doing Qualitative Research: A Practical Handbook,
(Sage Publications Inc.: London).
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Qualitative and Quantitative Approaches, Applied Social Research
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48. ...... references ..........
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