mixed methods latest
TRANSCRIPT
DEFINITION
Mixed methods research combines
quantitative and qualitative approaches by
including both quantitative and qualitative
data in a single study.
PURPOSE
To build on the synergy and strength that exists
between quantitative and qualitative research
methods.
To understand a phenomenon more fully than is
possible using either quantitative or qualitative
methods alone.
“Mixed methods research allows the use of both words and
numbers to obtain a better understanding” (Caracelli & Greene, 1993).
“Results can be generalized through the use of quantitative data
while providing individual voices through the use of qualitative
data” (Tashakkori & Teddlie, 2003).
“mixed methods research creates a deeper understanding of
research by using the strengths of qualitative and quantitative
research to inform both” (Creswell & Plano Clark, 2007)
Deductive approach
Concerned with objective
reality that is there to be
discovered.
Establishing cause-effect
relationship.
Identify hypotheses to test.
Inductive approach
Focus on interpreting theirparticipants’ perspectives.
Describing and understandingrelationships.
Work with guiding hypothesisand allow specific focus toemerge as a study progresses.
C H A R A C T E R I S T I C S O F Q UA N T I TA T I V E
& Q UA L I TA T I V E R E S E A R C H
QUANTITATIVE QUALITATIVE
a) QUAL - Quan Model
Also known as exploratory mixed methods design.
Qualitative data are collected first and are moreheavily weighted than quantitative data.
In the first phase of this model, observation andopen-ended interviews with individuals or groups areconducted and concepts and potential hypotheses areidentified.
In the second phase , variables are identified from concepts
derived from the qualitative analysis and hypotheses are
tested with quantitative techniques.
When qualitative methods are dominant, qualitative
researchers may decide to include survey, census, and Likert-
scale data along with narrative data.
The validity of the qualitative results can be enhanced by
the quantitative results.
(b) QUAN-Qual Model
Also known as the explanatory mixed methodsdesign.
Quantitative data are collected first and are more heavilyweighted than qualitative data
In the first study or phase, the researcher formulates ahypothesis, collects quantitative data and conducts dataanalysis.
The findings of the quantitative study determine the type
of data collected in a second study of phase that includes
qualitative data collection, analysis and interpretation.
The researcher can then use the qualitative analysis and
interpretation to help explain or elaborate on the quantitative
results.
(c) QUAN-QUAL Model
Also known as the triangulation mixed methods design.
In this model, quantitative and qualitative data are equally
weighted and are collected concurrently throughout the
same study-the data are not collected in separate studies or
distinct phases, as in the other 2 methods..
one of the most difficult aspects of any
research endeavor is the analysis of data.
Creswell developed a comprehensive
overview of mixed methods design data
analysis & interpretation procedures (pg 487, Table
19.3)
There were some examples of analytic &
interpretation procedures of types of mixed methods
designs ( triangulation, explanatory & explanatory)
Example 1. Quantifying qualitative data: Quanlitative data are coded, codes are assigned numbers, and the numbers of times codes appear are
recorded as numeric data. Quantitative data are descriptively
analyzed for frequency of occurrence. The two data sets are
compared.
Set of Frequency ofQuestionnaires Occurrence
Interview Codes thatcounted
for frequencies
QUANdata
collection
QUALdata
collection
QUAN data analysis
QUAL Data analysis
Compare & Interrelate
two QUAN data sets
InterpretationQUAN+QUAL
Example 2. Quantifying quantitative data: Quantitative data from
questionnaires are factor-analyzed. These factors then become
themes and then are compared with themes analyzed from
qualitative data.
Observation Identify theme
Questionnaires Factor
QUALdata
collection
QUANdata
collection
QUANdata
analysis
Compare &InterrelateData sets
QUALdata
analysis
Example 1. Explaining results: Conduct a quantitative survey to identify how
or more groups compare on a variables. Follow up with
qualitative interviews to explore the reasons why these
differences were found
Interview
QUANdata
collection
QUANresult
qualdata
analysisqualdata
collection
InterpretationQUAN qual
Identify result
for follow up
QUANdata
analysis
qualresult
Example 1. Developing an instruments: Obtain themes & specific statements
from individuals that support the themes. In the next phrase, use
these themes & statements to create scales & items as a
questionnaire. Alternatively, look for existing instruments that
can be modified to fit the themes & statements found in the
qualitative exploratory phase of the study. After developing the
instruments, test it out with the sample of population.
Develop Instrument
InterpretationQUAL quan
quandata
collection
quanresult
quandata
analysis
QUALresult
QUALdata
analysis
QUALdata
collection
Characteristics that help to identify a study as having a mixed
method design:
The study title
The data collection section
The purpose statement or the research questions
The researchers indicates the preference given to qualitative
or quantitative data collection
The researchers indicates the sequence in which qualitative ,
quantitative or both types of data were collected
The researchers describes how data were analyzed using both
quantitative and qualitative strategies.
Evaluating a mixed methods study :A mixed method study can be evaluated by answering questions related to ;
the use of at least one qualitative & one quantitative research method
the rational for using a mixed methods research design
the priority & sequence given to qualitative & quantitative data
collection
The use of qualitative & quantitative research questions and matching data collection techniques
The use of appropriate data analysis techniques for mixed designs