2. Mixed methods research (MMR)
involves collecting and integrating quantitative and qualitative data in a
single project and therefore may result in a more
comprehensive understanding of the phenomenon under
investigation.
Methodologically, MMR approaches rely on
1. combining deductive and inductive designs to generate
both quantitative and qualitative data, and
2. integrating the datasets in some way.
These approaches are appropriate when your purpose is to
describe, explain, or evaluate, and are particularly useful for
studying complex problems or issues.
3. Structure of a Research Proposal
The mixed methods paradigm is extremely diverse methodologically and theoretically.
Every research proposal will look somewhat different, just as each project will follow a
different plan. However, to some extent, even if the order and weight differ, research
proposals typically include most of what is suggested in Template 6.1
4. Basic Introductory Information
Title
MMR titles clearly state the main research problem and the
mixed methods design.
Abstract
In MMR this 150- to 200-word overview of the study typically
includes the problem or phenomenon you are studying, the
research purpose, basic information about the methods (noting
the mixed methods design), the participants, and why a mixed
methods study on the topic is needed.
Keywords
Five to six keywords let readers know the main problem, the
guiding theory (if applicable), and the mixed methods design.
5. The Topic
The Topic under Investigation
MMR is problem-centered with the research problem guiding all aspects of
research design. Clearly state the phenomenon under inquiry. You may identify
different dimensions of the topic as appropriate.
Research Purpose Statement
Briefly state the primary purpose(s) or objective(s) of the study. Include
the research topic (phenomenon), the participants and setting, the
methodology (quantitative and qualitative data collection methods, the
selected mixed methods design, and the theoretical framework guiding the
study as applicable), and the primary rationale for conducting the research.
For example, qualitative interviews may be used to explore the topic and
then develop an experimental intervention aimed at explanation
6. The Topic
Research Questions and Hypotheses (as Applicable)
MMR necessarily involves at least one quantitative research question or
hypothesis, at least one qualitative research question, and generally at least
one mixed methods question (although there are published studies that do not
include a mixed methods question.
Bear in mind that in order to effectively conduct MMR analysis, it is
necessary to have integrated research questions (Brannen & O’Connell, 2015;
Yin, 2006).
Integration can take various forms. Depending on a number of factors,
including the specific research purpose, the type of design used, and whether
the same participants are used for the different components of the research,
the quantitative and qualitative questions will be linked, but to various
degrees and in different ways.
7. The Topic
Research Questions and Hypotheses (as Applicable)
The MMR question(s) directly addresses the mixed methods nature of the study by asking something about
what is learned by combining the quantitative and qualitative data, or it may ask something about how
the mixed methods design aided the research project. These questions may employ relational language,
aimed at addressing the relationship between the quantitative and qualitative phases of research,
including words and phrases such as synergistic, integration, connection, comprehensive, fuller
understanding, and better understanding.
Given the complexity of question formulation in MMR, here’s an example:
• Study: A mixed methods study of college students’ attitudes regarding gender roles (combining survey
research and in-depth interviews)
• Quantitative hypothesis: Male undergraduates have more traditional attitudes about gender roles than
female undergraduates.
• Qualitative question: How do male and female undergraduates describe their views on gender roles?
• Mixed methods question: How did the combination of survey research and in-depth interviews provide a
more comprehensive understanding of male and female college students’ attitudes about gender roles?
8. The Topic
Philosophical Statement and Theoretical Perspective
MMR developed as a problem-centered approach to research
design. Additionally, by utilizing both quantitative and
qualitative approaches, mixed methods researchers necessarily
embrace and draw on the very different assumptions guiding
both practices.
MMR therefore relies on what Jennifer Greene calls “a mixed
methods way of thinking,” which necessarily assumes that
there are “multiple legitimate approaches to social inquiry”
(2007, p. 20). A mixed methods way of thinking values
“multiple ways of seeing and hearing, multiples ways of
making sense of the social world, and multiple standpoints on
what is important and to be valued” (Greene, 2007, p. 20).
9. The Topic
Pragmatism
is an American philosophical belief system that developed at the start of
the 20th century out of the work of Charles Sanders Peirce (1839–1914),
William James (1842–1910), John Dewey (1859–1952), and George Hebert
Mead (1863–1931) (Biesta & Burbules, 2003; Greene, 2007; Hesse-Biber,
2015; Patton, 2015).
“focus on the outcomes of action” (Morgan, 2013, p. 28), suggesting that
whatever theories are useful in a particular context are thereby valid.
The major criteria for design decisions are that they be “practical,
contextually responsive, and consequential” (Datta, 1997, p. 34).
Leaders in the field, Abbas Tashakkori and Charles Teddlie (1989), state that
pragmatism supports using both qualitative and quantitative methods,
places the research question(s) at the center of inquiry, and links all
methodological decisions to the research question(s).
10. The Topic
Pragmatism
R. Burke Johnson and Anthony J. Onwuegbuzie (2004, p. 18)
list the following among the primary features of pragmatism:
• The natural/physical world as well as the social and
psychological world (including subjective thoughts) are both
recognized.
• Knowledge is both constructed and based on the reality of the
world we experience and live in.
• Theories are valuable instrumentally; they are true to the
extent that they are applicable in a particular circumstance.
• Action is emphasized over philosophizing.
11. The Research Plan
Literature Review
An MMR literature review provides a foundation for readers to
understand what is already known about the topic through a
synthesis of the recent and landmark studies. This type of
literature review is complex, drawing on prior quantitative,
qualitative, and mixed methods research. If there is a gap in
previous research, such as a lack of quantitative, qualitative,
and/or MMR, note this and how the proposed study will fill the gap
in research on this topic.
The literature review should also include relevant theories
(and their origins) and conceptual frameworks (as applicable).
Because you are not bound to any particular set of theories or
disciplinary bodies in MMR, Sharlene Hesse-Biber (2010, p. 39)
suggests considering the following questions when reviewing
literature for a mixed methods study:
12. The Research Plan
Literature Review
• How are topics defined in the research?
• What key terms and phrases do authors employ?
• How have other researchers approached the topic?
• What controversies emerge in the literature?
• What are the most important findings from the
literature?
• What findings seem most relevant to your interests?
• What pressing questions still need to be addressed
concerning your topic?
• Are there gaps in the literature?
13. The Research Plan
Design and Methods of Data Collection
There are three primary types of design: sequential, convergent,
and nested.
Sequential and nested models each offer two design options, for a
total of five primary design types. As these types of designs are
reviewed, bear in mind that the type of design you select should be
directly linked to your research purpose and questions.
In particular, consider the following:
• Why are you collecting both quantitative and qualitative data?
• What is the relationship between the quantitative and qualitative
aspects of the study?
• In what ways will the two datasets inform each other? Put
differently, how and to what extent will you integrate the two datasets
during data collection and/or analysis?
14. The Research Plan
Design and Methods of Data Collection
Integration refers to how the researcher relates the quantitative and
qualitative datasets. There is a continuum of integration. That is, the
extent to which the two methods and datasets are related to each other
varies. At one end of the continuum there are “component designs” (in
which integration occurs only during data analysis and interpretation)
(Greene, 2007; Maxwell et al., 2015). Component designs offer minimal
integration. At the other end of the continuum there are “integrated
designs” (in which integration is built into the entire design structure)
(Greene, 2007; Maxwell et al., 2015). Integrated designs offer maximum
integration (see Figure 6.1).
15. The Research Plan: Design and Methods of Data
Collection
Five primary mixed methods designs
1. Sequential designs are based on time order, with either the quantitative or
qualitative data collection phase preceding the other. Creswell (2015) identifies
two basic sequential designs (with numerous possible adaptations to suit a
particular study): explanatory sequential designs and exploratory sequential
designs.
2. Explanatory sequential designs begin with quantitative methods, which are
followed up by qualitative methods designed to explain the quantitative findings
in depth (Creswell, 2015; see Figure 6.2).
16. The Research Plan: Design and Methods of Data
Collection
Exploratory sequential designs begin with exploring a topic
through qualitative methods and then using the findings to
develop a quantitative instrument and phase of the research
study (Creswell, 2015).
This approach is commonly used when the topic or the
population of interest is under researched (Creswell, 2015; see
Figure 6.3).
17. The Research Plan: Design and Methods of Data
Collection
Janice M. Morse suggests that MMR includes a core and
supplemental method.
Under this typology, uppercase words denote the primacy of the
method within the study, and lowercase words denote secondary
status (see Morse 1991, 2003)3:
QUANT: Quantitative method is core
QUAL: Qualitative method is core
quant: Quantitative method is supplemental
qual: Qualitative method is supplemental
18. The Research Plan: Design and Methods of Data
Collection
David Morgan (1998) embraces Morse’s typology and suggests four
sequential designs based on both time order and priority (the relative
importance of each method within the study). The assumption guiding
these designs is that in a given study, either the quantitative or
qualitative phase may be dominant.
Design 1: qual followed by QUANT
Design 2: quant followed by QUAL
Design 3: QUANT followed by qual
Design 4: QUAL followed by quant
Morse’s (1991, 2003) notation system also employs arrows to denote
the time sequence and direction of sequential designs.
For example: QUANT → qual
QUAL → quant
19. The Research Plan: Design and Methods of Data
Collection
4. Convergent or concurrent designs4 involve collecting both
quantitative and qualitative data, analyzing both datasets, and
then integrating the two sets of analyses in order to cross-
validate or compare the findings (Creswell, 2015; see Figure
6.4).
Morse’s (1991, 2003) notation system denotes convergent
data collection with a plus sign. For example:
QUANT + QUAL
20. The Research Plan: Design and Methods of Data
Collection
5. Nested designs are those in which one method is used as the
primary method, and additional data are collected using the
secondary method (Creswell, 2003; Hesse-Biber & Leavy, 2011).
Nesting qualitative data in quantitative designs involves
using a quantitative method (e.g., an experiment) as the
primary method and nesting a qualitative component in the
design (see Figure 6.5).
21. The Research Plan: Design and Methods of Data
Collection
5. Nested designs are those in which one method is used as the primary
method, and additional data are collected using the secondary method
(Creswell, 2003; Hesse-Biber & Leavy, 2011).
Nesting quantitative data in qualitative designs involves using a
qualitative method (e.g., field research) as the primary method,
and nesting a quantitative component in the design (see Figure
6.6).
22. The Research Plan: Design and Methods of Data
Collection
Summary of the different mixed method designs.
23. The Research Plan:
Sampling and Participants
In which populations are you interested in learning?
How will you access members of that population?
Who will your participants be?
What size samples will you draw for the quantitative and
qualitative aspects of the study?
If the qualitative sample is smaller, will it be drawn from
the quantitative sample, or will you seek different
participants for the two aspects of the study?
How will your sampling strategies maximize the reliability
and generalizability or transferability of your findings?
24. The Research Plan:
Sampling and Participants
First, identify the population about which you are
interested in later making claims.
Next, identify the study population, the group of elements
from which you will actually draw your sample(s).
You also need to determine the size of your samples.
Table 6.2, presents common sampling protocols, bearing in
mind there could be any number of reasons or constraints
that force you to make other choices.
26. The Research Plan:
Data Analysis and Interpretation Strategies
Data analysis and interpretation are particularly
challenging in MMR. First, you need to prepare and
organize both sets of data. Quantitative data are entered
it into a spreadsheet or statistical software program.
Qualitative data may need to be transcribed, scanned,
sorted, organized in a repository, and entered into a
CAQDAS.
Three issues to consider include
(1) integration
(2) comparability, and
(3) data transformation.
27. The Research Plan:
Data Analysis and Interpretation Strategies
Data analysis and interpretation are particularly
challenging in MMR. First, you need to prepare and
organize both sets of data. Quantitative data are entered
it into a spreadsheet or statistical software program.
Qualitative data may need to be transcribed, scanned,
sorted, organized in a repository, and entered into a
CAQDAS.
Three issues to consider include
(1) integration
(2) comparability, and
(3) data transformation.
28. The Research Plan: Data Analysis and Interpretation
Strategies
Beginning with integration, Julia Brannen and Rebecca O’Connell (2015, p. 260)
identify five possible frameworks for integration that occurs at the analysis
phase:
1. Corroboration: One set of findings is confirmed by the other.
2. Elaboration or expansion: One type of data analysis contributes to the
understanding gained by another.
3. Initiation: The use of the first method leads to new research questions or
hypotheses, which are then investigated with the second method (in this
case, the initial dataset is analyzed before the second method is
implemented).
4. Complementarity: The quantitative and qualitative findings are
juxtaposed to “generate complementary insights” and produce a more
comprehensive understanding.
5. Contradiction: The quantitative and qualitative findings conflict with each
other, and you explore the contradiction or juxtapose the two sets of findings
for others to explore or privilege one set of findings over the other.
29. The Research Plan: Data Analysis and Interpretation
Strategies
A second issue to consider is comparability. If your goal is to
compare the quantitative and qualitative findings, you must
consider the extent to which your sampling strategies allow for
such comparisons.
Data transformation
The term used when quantitative data are transformed into
qualitative data, or vice versa—a heuristic device to assist in
analysis (Brannen & O’Connell, 2015; Caracelli & Greene, 1993;
Two forms of data transformation:
1. Quantizing is the process of transforming qualitative data into
quantitative data (transforming qualitative codes into quantitative
variables). CAQDAS programs can assist in the creation of variable
data based on qualitative data, which can then be exported for
statistical analysis (Hesse-Biber & Leavy, 2011; Sandelowski, Volis,
& Kraft, 2009).
31. The Research Plan: Data Analysis and Interpretation
Strategies
2. Qualitizing is the process of transforming
quantitative data into qualitative data
(transforming quantitative variables into qualitative
codes) (Tashakkori & Teddlie, 1998).
32. The Research Plan
Representation:
Identifies your intended audience(s) and a format
to represent your findings to that audience. Also
notes how you will present all three sets of
findings—qualitative, quantitative, and mixed
methods (the additional insights gained by the
mixed approach)—such as back-to-back
subsections in the report or side-by-side displays
of the quantitative and qualitative findings,
followed by a mixed methods discussion.
33. The Research Plan
Ethics Statement:
Discusses the ethical substructure of your project,
addressing your values system, ethical praxis, and
reflexivity.
References:
Includes a full list of citations, properly crediting all
those from whom you’ve borrowed ideas or quoted.
Follow your university reference style guidelines (if
applicable) or the norms within your discipline.
34. The Research Plan
Appendices:
Includes your proposed timeline, budget, copies
of your recruitment letters and informed consent,
permissions, and copies of all instruments (e.g.,
pretests, survey instruments [questionnaires],
experimental interventions, measuring
instruments, interview guides, posttests).
35. The Research Plan
Conclusion
As discussed in this chapter, MMR is particularly
useful for learning about a complex phenomenon and
research problems through both deductive and inductive
means. MMR allows us to provide a comprehensive
understanding of the phenomenon under investigation
by collecting and, in some way, integrating quantitative
and qualitative data in a single project. This approach
adopts a pragmatic stance, prioritizing the research
problem and using methods and theories instrumentally,
based on their applicability.
