This document provides an overview of mixed methods research. It defines mixed methods as an approach that involves collecting and analyzing both quantitative and qualitative data to better understand research problems. The document discusses key aspects of mixed methods research such as common designs, advantages and challenges. It also covers topics like paradigm assumptions, strategies for mixing methods, and evaluating mixed methods studies. Major mixed methods designs introduced include convergent parallel, explanatory sequential, and exploratory sequential designs.

1. MIXED METHODS RESEARCH
Dr Nooredin Mohammadi
nooredin.mohammadi@yahoo.com

2. DISCLOSURE
I disclose that the most part of content in this presentation is
adapted from the following reference.
• Creswell, J. W., & Plano Clark, V. L. (2017). Designing and conducting
mixed methods research (3rd edition). Thousand Oaks, CA: Sage
Publications.

3. LEARNING OBJECTIVES
• Define mixed methods research
• Discuss research problems which fit mixed methods
• Outline advantages of and challenges in using mixed methods
• Discuss choosing a mixed methods design
• Introduce major mixed method designs
• Evaluate a mixed method study

4. INTRODUCTION
• Acquire knowledge and understand realities
• Research and research paradigm
• Paradigm is “the set of common beliefs and agreements shared
between scientist about how problems should be understood and
addressed (Kuhn, 1970)
• Research paradigms can be characterized by the way scientists
respond to three basic questions: ontological, epistemological
and methodological questions (Guba, 1990)

5. BASIC QUESTIONS OF PARADIGM
• Ontological question
• What is reality?
• Epistemological question
• What and how can we know reality/knowledge?
• Methodological Question
• What procedures can we use to acquire knowledge?

6. RESEARCH PARADIGMS
• Different research paradigms
• Positivism
• Interpretivism (Constructivism)
• Pragmatism
• Critical theory (ideology)
• Realism

7. Adapted from Saunders et al. 2015
RESEARCH ONION

8. RESEARCH APPROACHES
• Emergence of research methodology approaches
• Quantitative research approach (1900-1940)
• Qualitative research approach (1960-2000)
• Mixed approach (1980-2000)

9. Assumptions of Approach Quantitative Research Approach Qualitative Research Approach
Ontological
Perception of reality
Single objective world Multiple subjectivity derived realities
coexist
Epistemological
Theory of knowledge
Researchers are independent from the
variables under study
Researchers interact with phenomenon
Axiology
Study of underlying values
Researchers act in a value-free and
unbiased manner
Researchers act in a value-laden and
biased fashion
Rhetorical
Use of language
Use impersonal, formal and rule-based
text
Use personalised, informal and context-
based language
Methodological
Researcher use deduction, cause-and-
effect relationship and context-free
methods
Research use induction, multi process
intervention, context-specific method

10. Research
Methodologies
Qualitative
Quantitative
Monomethod
Multimethod
Monomethod
Multimethod
Mixed Method
Adapted from Creswell and Clark, 2017

11. • Several definitions for mixed methods
• Focus of the definition
• Research paradigms
• Research methodology
• Research methods
• Research purpose
DEFINITION OF MIXED METHODS

12. DEFINITION
Mixed methods
A research design with philosophical assumptions as well as methods of inquiry
As a methodology, involves philosophical assumptions that guide the direction of
collection and analysis and the mixture of qualitative and quantitative approaches
in many phases of the research process.
As a method, focuses on collecting, analysing, and mixing both quantitative and
qualitative data in a single study or series of studies. Its central premise is that
the use of quantitative and qualitative approaches, in combination, provides a
better understanding of research problems than either approach alone
(Creswell and Plano Clark, 2017; 5)

13. • Rumi poetry
BETTER UNDERSTANDING

14. MIXED METHODS
• What is NOT mixed methods research?
• Simply using the name without the rigorous methods
• Having both quantitative and qualitative data available
• Collecting and reporting quantitative and qualitative data
separately without combining them
• Using multiple quantitative approaches or multiple qualitative
approaches

15. MIXED METHOD CORE FEATURES
• Collect and analysis both quantitative and qualitative data in
response to research question
• Using rigorous quantitative and qualitative methods
• Combing or integrating quantitative and qualitative data
• Development and using a specific type of mixed methods design
• Framing the mixed methods design within a broader framework
(theory or philosophy)

16. WHAT RESEARCH PROBLEMS
FIT MIXED METHODS?

17. PROBLEMS FIT MIXED METHODS
• One data source insufficiency
• Explain initial results
• Generalise exploratory findings
• Enhance a study with a second method
• Best employ a theoretical stance
• Understand a research object through multiple research phases

18. MIXED METHODS ADVANTAGES
• Offset the weakness of quantitative and qualitative research
• Personal interpretation and the researcher bias
• Difficulty in generalising findings due to small sample size
• Enable to use all available data collection tools
• Answer to questions (not answer by one of the research approaches)
• Bridge across divide between qualitative and quantitative
• Using multiple paradigms

19. CHALLENGES IN MIXED METHODS
• Researcher skills
• Experience with both quantitative and qualitative research
• Time and resources
• Feasible in terms of time length and expenses
• Convincing others
• Object to relatively new approach

20. CHOOSING A MIXED
METHODS DESIGN?

21. MIXED METHODS DESIGNS
• Mixed methods designs are procedures for conducting a study
• Equivalent to RCTs in quantitative research or ethnographies in
qualitative research

22. PRINCIPLES FOR DESIGNING
• Recognise that mixed methods design can be fixed or emergent
• Identify an approach to design (typology-based or dynamic)
• Match the design to the research problem, purpose and question
• Be explicit about the reasons for mixing methods

23. STUDY STRANDS
• Example of quantitative and qualitative strands in a mixed methods study
Quantitative
State quantitative Question
Collected quantitative data
Analyse quantitative data
Interpret quantitative results
Qualitative
State qualitative Question
Collected qualitative data
Analyse qualitative data
Interpret qualitative results
Overall
interpretation
Adapted from Creswell and Clark, 2017

24. KEY DECISIONS
• Four key decisions in choosing a mixed methods design
• Level of interaction between quantitative and qualitative strands
• Priority of the quantitative and qualitative strands
• Timing of the quantitative and qualitative strands
• Where and how to mix the quantitative and qualitative strands

25. LEVEL OF INTERACTION
• The two study components are
• Independence
• Interactive

26. PRIORITY OF TWO METHODS
• Three possible weighting options for a mixed method design
• Equal priority
• Quantitative priority
• Qualitative priority

27. TIMING OF TWO METHODS
• Timing is classified into three ways
• Concurrent timing
• Sequential timing
• Multiphase combination timing

28. WHERE AND HOW TO MIX
• Mixing strategies
• Mixing during interpretation
• Mixing during data analysis
• Mixing during data collection
• Mixing at the level of design

29. PROTOTYPES OF MAJOR DESIGNS
• Convergent mixed method design
• Explanatory mixed method design
• Exploratory mixed method design
• Embedded mixed method design
• Transformative mixed method design
• Multiphase mixed method design

30. CONVERGENT PARALLEL DESIGN
Quantitative data
collection and analysis
Qualitative data
collection and analysis
interpretation
Compare or
relate
Adapted from Creswell and Clark, 2017

31. • Collect and analyse two independent strands of quantitative and
qualitative data at the same time, in a single phase
• Prioritize the methods equally
• Keep the data analysis independent
• Mix the results during the overall interpretation
• Try to look for convergence, divergence, contradictions, or
relationships of two sources of data
CONVERGENT PARALLEL DESIGN

32. • In quantitative and Qualitative studies
• Research questions create parallel
• Different or same sample groups
• Equal or unequal sample sizes
• Data collets from one source or different sources of data
• Merged data analysis strategies
• Side-by-side comparison
• Joint display
• Data transformation merged analysis
CONVERGENT PARALLEL DESIGN

33. • Purpose
• Better understanding and more development of the research problem
by obtaining different complementary data
• Validation purpose
• Example: A study of Iran University of Medical Sciences nursing students’
attitudes towrads COVID-19 vaccination.
CONVERGENT PARALLEL DESIGN

34. • Needs both quantitative and qualitative expertise
• Consequences of having different samples and different sample size
when merging two data sets
• How to merge two types of data
• How to deal with the situation in which quantitative and qualitative
results contradict each other
CHALLENGES

35. EXPLANATORY SEQUENTIAL DESIGN
Quantitative
data collection
and analysis
Follow up
with
Qualitative data
collection and
analysis
Interpretation
Adapted from Creswell and Clark, 2017

36. • Typically two-phase design
• Collect quantitative and qualitative data at different time
• Qualitative study depends on quantitative results
• The priority of quantitative data collection
• Collect and analyse quantitative data
• Identify specific quantitative results that need additional explanation
• Design qualitative study based on what learn from quantitative results
• Collect and analyse qualitative data
• Interpret combined results
EXPLANATORY SEQUENTIAL DESIGN

37. • Purpose
• To use qualitative approach to explain quantitative results (significant, non-
significant, outliers or surprising results) or to guide to form groups based
on quantitative results
• Example: Iran University of Medical Sciences nursing students’ persistence in a
distributed PhD program in nursing
EXPLANATORY SEQUENTIAL DESIGN

38. • Time consuming
• Decisions about which quantitative results need further explanation
• Decisions about who to sample and what criteria used for sample
selection for qualitative study
CHALLENGES

39. EXPLORATORY SEQUENTIAL DESIGN
Quantitative
data collection
and analysis
Builds to
Qualitative data
collection and
analysis
Interpretation
Adapted from Creswell and Clark, 2017

40. • Typically it is a two-phase design
• Three phases for instrument development (instrument development phase,
a phase testing, and apply the instrument)
• Collect quantitative and qualitative data at different time
• Qualitative results can help and inform the second quantitative
method
EXPLORATORY SEQUENTIAL DESIGN

41. • Purpose
• The qualitative phase is used to help develop or inform the quantitative
study.
• Instrument design (explore)
• Grounded theory (generalize qualitative results)
• Example: exploring the dimensions of organizational assimilation of new
academic staffs in Nursing and Midwifery Faculty, Iran University of Medical
Sciences
EXPLORATORY SEQUENTIAL DESIGN

42. • Considerable time to implement a new instrument
• Small purposeful sample in the first phase and large sample of
different participants in the second phase
• Decision which data to use from the qualitative phase to build the
quantitative instrument
• Develop valid and reliable scores on the instrument
CHALLENGES

43. EMBEDDED DESIGN
Quantitative (or Qualitative) Design
Quantitative (or Qualitative) data collection and analysis
qualitative (or quantitative) data collection
and analysis (before, during or after)
Interpretation
Adapted from Creswell and Clark, 2017

44. • A quantitative or qualitative data collection is within a quantitative
or qualitative procedure.
• A single data set is not enough.
• Two types of data answer different research questions.
• The collection and analysis of the second data set may occur before,
during, and/or after the first data collection.
EMBEDDED DESIGN

45. • Purpose
• To answer different questions that requires different types of data
• Example: effectiveness of problem-based learning in nursing
education
EMBEDDED DESIGN

46. • Must specify the purpose of collecting qualitative (or quantitative)
data as a part of a larger quantitative (or qualitative) study
• Must decide at what point in the experimental study to collect the
qualitative data
• Difficult to integrate the results when the two methods are used to
answer different research questions
• Potential treatment bias in intervention experiment due to collected
qualitative data
CHALLENGES

47. TRANSFORMATIVE DESIGN
Quantitative
data collection
and analysis
Follow up
with
Qualitative
data collection
and analysis
Interpretation
Adapted from Creswell and Clark, 2017
Transformative Framework

48. • More relates to the content than to the methodology
• Can implement any of four basic mixed methods designs within the
transformative framework.
• Purpose
• To address issues of social justice and call for change for underrepresented
or marginalized populations.
• Example: A story of women’s professional power in nursing
TRANSFORMATIVE DESIGN

49. • Little guidance in the literature to assist researchers with
implementing mixed methods in a transformative way
• Needs to have expertise in theoretical foundations of the study
CHALLENGES

50. MULTIPHASE DESIGN
Study 1
Qualitative
informs Study 2
Quantitative
Informs
Study 3
mixed
methods
Overall program objective
Adapted from Creswell and Clark, 2017

51. • Challenges associated with individual concurrent and sequential
designs.
• Needs sufficient resources, time, and effort.
• May need a research team to implement research
• Examples: assessing nursing students’ understating of and reactions to
stress in different ethnic cultures
CHALLENGES

52. • Isolate three basic designs
• Convergent design
• Explanatory sequential design
• Exploratory sequential design
• Applied core designs in
• Other designs (experiment/intervention trial)
• Other theories (feminist theory)
• Other methods (community-based participatory action research)
ADVANCES MIXED METHODS DESIGN

53. • Content vs methods picture
• Added features
• Change-implementation matrix
ADVANCES MIXED METHODS DIAGRAM

54. MIXED METHODS POPULARITY
25+ books on mixed method research since 2016

55. • Qualitative and quantitative evaluation criteria
• Mixed methods evaluation criteria
• Collect and analyse both qualitative and qualitative data in rigorous method
• Integrates, mixes (merges, embedded, connects) the two sources of data
• Include the use of mixed methods research design
• Frames the study within philosophical assumptions
• Using mixed methods terms consistently
EVALUATING A MIXED METHODS

56. TERMINOLOGY
QUAN or quan refers to quantitative
QUAL or qual refers to qualitative
Use of upper case refers to emphasis, primary or dominant method
Lower case refers to lower emphasis, priority or dominance
MM refers to mixed methods
“→” data collected sequentially
“+” data collected simultaneously
“=“ converged data collection
“( )” one method embedded in the other
Adapted from Creswell and Clark, 2017

57. BIBLIOGRAPHY
• Creswell, J. W., & Clark, V. L. P. (2017) Designing and conducting mixed methods research.
Sage publications.
• Guba, E. G., & Lincoln, Y. S. (2005) Paradigmatic Controversies, Contradictions, and
Emerging Confluences. In N. K. Denzin & Y. S. Lincoln (Eds.), The Sage handbook of
qualitative research (p. 191–215), Sage Publications Ltd.
• Kuhn, T. S. (1962) The structure of scientific revolutions. Chicago, The University of
Chicago Press.
• Saunders, M., Lewis, P. & Thornhill, A. (2015) Research Methods for Business Students
7th edition, Pearson Education Limited