Transcript Mixed Methods Research

Triangulation
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• Triangulation is a powerful technique that facilitates validation of
data through cross verification from more than two sources. In
particular, it refers to the application and combination of several
research methodologies in the study of the same phenomenon.[2]
• By combining multiple observers, theories, methods, and empirical
materials, researchers can hope to overcome the weakness or
intrinsic biases and the problems that come from single method,
single-observer and single-theory studies.
http://en.wikipedia.org/wiki/Triangulation_(social_science)
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Triangulation Techniques
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Data Triangulation
Investigator Triangulation
Theory Triangulation
Methodological Triangulation
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Mixed methods research
• A style of research that uses procedures for
conducting research that are typically applied in
both quantitative and qualitative studies
• The purpose of these designs is to build upon
the synergy and strength that exists between
quantitative and qualitative methods in order to
more fully understand a given phenomenon than
is possible using either quantitative or qualitative
methods alone
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• Mixed methods provides a clearer picture
of what is happening in the real world.
– Quantitative data give you some numbers to
work with.
– Qualitative data give you an explanation of
the numbers.
– Together they provide a way of triangulating
data to confirm findings.
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• The research problem itself determines
the choice of a design and method
– Using surveys to identify specific groups of
students and conducting focus groups with
them to understand their views
– A series of interviews are conducted to
ascertain the critical issues bothering
students, and a survey of the student body is
conducted using these issues as variables
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A Quick Review
• Quantitative
research
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Deductive approach
generalizable
Causal relationships
Identify and test
hypotheses
– Random selection of
participants
• Qualitative
research
– Inductive approach
– Participant’s
perspectives
– Describing and
understanding
relationships
– Emerging questions
– Purposive sampling
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Inductive
Reasoning
Deductive
Reasoning
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Mixed methods is not that different
from other methods
Identifying a research problem
Reviewing the literature
Identifying a purpose
and stating questions
Collecting data
Analyzing and interpreting data
Reporting and evaluating the study
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Preliminary Design Considerations
(Morse, 1991)
Approach
QUAL + quant
QUAL >>> quant
QUANT + qual
QUANT>>>qual
Type
Purpose
Limitations
Resolutions
Simultaneous
Enrich description of
sample
Qualitative sample
Utilize normative data
for comparison of
results
Sequential
Test emerging H,
determine distribution of
phenomenon in population
Qualitative sample
Draw adequate
random sample from
same population
Simultaneous
To describe part of
phenomena that cannot be
quantified
Quantitative sample
Select appropriate
theoretical sample
from random sample
Sequential
To examine unexpected
results
Quantitative sample
Select appropriate
theoretical sample
from random sample
Which model did we use?
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Parsimonious Designs (Creswell & Plano Clark, 2007)
Concurrent Mixed Methods Designs
Triangulation Design
QUAN
Data &
Results
Interpretation
QUAL
Data &
Results
Embedded Design
QUAN
Pre-test
Data &
Results
Intervention
qual
Process
QUAN
Post-test
Data &
Results
Interpretation
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Sequential Designs Mixed Methods Designs
Explanatory Design
QUAN
Data &
Results
Following up
qual
Data &
Results
Interpretation
Exploratory Design
QUAL
Data &
Results
Building to
quan
Data &
Results
Interpretation
Sequential Embedded Design
Beforeintervention
qual
QUAN
Intervention
Trial
Afterintervention
qual
Interpretation
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MIXED METHODS RESEARCH: A discussion paper
JULIA BRANNEN
Institute of Education, University of London
Writing up mixed methods research
What models are there for writing up mixed methods research? The answer is that
there is a lack of exemplary studies that demonstrate different ways of writing up
evidence based on different methods. This is unsurprising since, as we have noted,
this is not straightforward. For one thing academic journals tend to be organised
around disciplines and may favour particular types of research. Moreover different
types of data analyses may sit awkwardly together on the published page and may
require rather a lot of space to justify their validity and credibility. Some researchers
using mixed methods may for such reasons report their qualitative and quantitative
results separately. Researchers presenting evidence based on both qualitative and
quantitative methods but drawing upon one set of evidence and under reporting the
other may risk criticism for not fully exploiting the possibilities for the analysis of
both data sets.
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Competition and Cooperation Among Working Women in the Context of
Structural Adjustment: The Case of Street Vendors in la Paz-El Alto, Bolivia
Victor Agadjanian Journal of Developing Societies 2002 18: 259
Abstract
This case study of women street vendors in La Paz-El Alto, Bolivia, examines the
dynamics of competition and cooperation among this group of poor working
women in the context of economic structural adjustment and political
pluralization. It is argued that the economic and political reforms not only
increase street vendors’ insecurities, but may also undermine the potential for
their broad-based solidarity and collective actions. Extreme competition in the
overcrowded street commerce, diminishing returns, and disillusionment with
traditional forms of workers’ organization hinder cooperation among street
vendors and fragment the social body of the street marketplace, often by further
reinforcing its gender, class, ethnoracial, and religious fault lines.
http://jds.sagepub.com/content/18/2-3/259.full.pdf
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