This document outlines different aspects of mixed method research design including definitions, types of designs, and strengths and limitations. It defines mixed methods as an approach that uses both quantitative and qualitative techniques. The main types of mixed method designs discussed are triangulation, embedded, explanatory, and exploratory designs. Triangulation design collects both quantitative and qualitative data concurrently to compare results. Embedded design has one data type play a supplemental role. Explanatory design starts with quantitative data collection and analysis followed by qualitative to explain results. Exploratory design starts with qualitative data to inform subsequent quantitative data collection. Strengths include using the advantages of both approaches while limitations include increased time and potential conflicting results.

1. Mixed Method
Research Design
Presented By:
Nida Ayub (PhD Scholar)
Mishal Fatima (PhD Scholar)

2. Outline
• Introduction
• Rational/ reasons of using mixed method design
• Aspects of mixed method study
• Notations
• Types of mixed method design
• Strengths and limitations

3. Definition OF
Research Design
Research
Design
Collecting
Analyzing
Interpreting
Reporting

4. Definition Mixed Method Design
Mixed
Method
Quantitative
Qualitative

5. 1. approach to investigating the social world
2. more than one kind of technique for gathering,
analyzing, and representing human phenomena

6. Example
To what extent does the
frequency of traffic
accidents (quantitative) reflect
cyclist perceptions of road
safety (qualitative) in
Amsterdam?
How do average hospital salary
measurements over
time (quantitative) help to
explain nurse testimonials about
job satisfaction (qualitative)?

7. Different Terms
Synthesis
Integrating
Quantitative
Qualitative
Methods
Multimethod
Mixed
Method
Design

8. Reasons for Use
Generalizability
Contextualization
Credibility

9. Key Factors to use
• What is research problem?
• Researcher must evaluate their own expertise
• Keep into consideration of available resources

10. Planning Mixed Methods Procedures
Timing Weighting
Mixing Theorizing

11. Timing
• consider the timing of their qualitative and quantitative data
collection.
• Data collection can occur in phases (sequentially) or
concurrently (at the same time).
• depending on the researcher's initial intent.
• If qualitative data is collected first, it is for the purpose of
exploring the topic with participants at sites.
• The researcher expands their understanding through a second
phase, collecting data from a large number of people
(typically a sample representative of a population).

12. Weighting
• weight or priority vary in a particular study.
• weight allocation equal in some studies or may emphasize
one over the other.
• The priority assigned to a particular type of research depends
on factors like the researcher's interests, the study's audience
(e.g., faculty committee, professional association), and the
emphasis the investigator wants to place on a specific aspect
of the study.

13. Mixing
• Two ways to follow for this:
1. One approach (Connected)
• involves keeping the two data sets separate but connected, such as using
quantitative data to identify participants for qualitative data collection in
a two-phase project.
2. Another method (Embedded)
• collect both types of data concurrently and integrate or merge them by
transforming qualitative themes into counts and comparing them with
descriptive quantitative data.

14. Theorizing
• the theories are found typically in the beginning sections as an
orienting lens that shapes the types of questions asked, who
participates in the study, how data are collected, and the implications
made from the study

15. Example
Connected
Depressive patients with
suicidal ideation (quantitative)
how they regulate their
impulses for not attempting
suicide (Qualitative).
Embedded
Mother’s grief for deceased
child and how they cope with
it.

17. Notations
CAPITALIZATION
Plus Arrow
Capitalization QUAN/QUAL

18. Example

20. Major Types
Triangulation Design
Embedded Design
Explanatory Design
Exploratory Design

21. Triangulation Research Design
purpose of this design is “to obtain different but complementary data on the same topic” (Morse, 1991,
p. 122) to best understand the research problem.
bring together the differing strengths and no overlapping weaknesses of quantitative methods
(large sample size, trends, generalization) with those of qualitative methods (small N, details,
in depth)
is used when a researcher wants to directly compare and contrast quantitative statistical
results with qualitative findings or to validate or expand quantitative results with
qualitative data

22. Quantitative
results
Qualitative
results
Merged for final results

23. Example
• Effects of screen time on children. (Qualitatively explore
the effects then quantify for further assessment of these
effects)
• A rural adolescent perceptions of alcohol and other drug
resistance.

24. Embedded Research Design
One data type
as supplemental
Provide
secondary
role
Single data
set not
sufficient

26. Example
• A study of the factors relating depression and diabetes as
moderated by race. A embedding qualitative interviews about
beliefs and experiences with depression for African American
patients with diabetes to help explain the predictive
relationships.
• Psychotherapeutic treatment of anger with help of Islamic
therapy.

27. Explanatory Research Design
starts with the collection and analysis of
quantitative data in the first phase
followed by the subsequent collection and
analysis of qualitative data in the second
phase.
second, qualitative phase of the study is
designed to connect to or follow from the
results of the first quantitative phase.
QUAL need
to explain
significant/n
onsignificant
results

29. Example
• doctoral students’ persistence in an online learning
environment.
• Initial quantitative phase, to identify factors predictive of
students’ persistence.
• In the second phase, qualitative multiple case study approach
to help explain why certain factors identified in the first phase
were significant predictors of student persistence in the
program.

30. Exploratory Research Design
the results of the first method are qualitative
and can help develop or inform the second
method, which is quantitative
Useful for exploration of
phenomenon, for test development,
existing no theory

32. Example
Young adults’ perceptions about the significance of the
self to others in romantic relationships.

33. Strength
1. Best of both worlds’
analysis
• Detailed
• contextualized insights
of qualitative data
• Generalizable
• externally valid insights
of quantitative data.
2. Method flexibility
• flexibility in designing
research
• combine different types of
studies to distill the most
informative results.

34. Limitations
Work load/ time
consuming
• Collecting, analyzing,
and synthesizing two
types of data into one
research product takes a
lot of time and effort.
Differing or conflicting
results
• quantitative and
qualitative results do not
agree or you are
concerned you may
have confounding
variables, it can be
unclear how to proceed.

35. References
• Creswell, J. W., Plano Clark, V. L., Gutmann, M., & Hanson, W. (2003). Advanced mixed
methods research designs. In A. Tashakkori & C. Teddlie (Eds.), Handbook of mixed
methods in social and behavioral research (pp. 209–240). Thousand Oaks, CA: Sage.
• Greene, J. C., Caracelli, V. J., & Graham, W. F. (1989). Toward a conceptual framework
for mixed-method evaluation designs. Educational Evaluation and Policy Analysis, 11(3),
255–274.
• Creswell, J. W. (2003). Data analysis strategies for mixed-method evaluation designs.
Educational Evaluation and Policy Analysis, 15(2), 195–207.
• Morgan, D. L. (1998). Practical strategies for combining qualitative and quantitative
methods: Applications to health research. Qualitative Health Research, 8(3), 362–376.
• Morse, J. M. (2006). Approaches to qualitative-quantitative methodological triangulation.
Nursing Research, 40, 120–123.
• 2007