MIXED METHODS

By,

Dr. Johan @ Eddy Luaran

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

TYPES OF MIXED METHODS

RESEARCH DESIGN

a) QUAL-quan model

b) QUAN-qual model

c) QUAN-QUAL model

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