Title: Qualitative Data Analysis: An introduction
1Qualitative Data Analysis An introduction
- Carol Grbich
- Chapter 22. Incorporating data from multiple
sources mixed methods
2Mixed Methods
- Key points
- The advantages of combining quantitative and
qualitative data are that you can maximize the
impact of both - For mixed methods to be successful, issues of
sampling, design, data analysis and data
presentation need careful attention - Two ways of mixing methods regarding design are
concurrent and sequential, but other new mixes
are emerging - Does qualitative data miss out in such a mix? and
what is the next move?
3A brief history of Qualitative and Quantitative
approaches
- The three stages of debate relating to
quantitative and qualitative approaches - 1. never the twain shall meet.
- 2. rapprochement
- 3. co-operation and mixing
4What are the major differences between
qualitative and quantitative?
- Qualitative is an inductive approach
-
- Questions tend to be exploratory and open ended
and data is often in narrative form. - Reality is seen as a shifting feast, subjectivity
is usually viewed as important - P power is shared with the participants who are
the experts on the matter under investigation. - Analysis predominantly deals with meanings,
descriptions, values and characteristics of
people and things. - The outcome sought is the development of
explanatory concepts and models - Widespread generalisation (apart from logical
generalisation that is from similar instance to
similar instance) is avoided.
5What are the major differences between
qualitative and quantitative
- Quantitative is deductive
- Reality is seen as static and measurable
-
- Objectivity (distance, neutrality) and linearity
(cause effect) may be sought - Outcomes are pre specified , hypotheses l dictate
questions and approach. - Researcher control of the total process is
paramount, precision and predictability are
important -
- Statistical approaches identify numbers and
clarify relationships between variables. - Theory testing is the key and generalisation and
predictability the desired outcomes. - Survey and experimental research are the main
design options. - Conclusions drawn follow logically from certain
premises - usually rule based - which are
themselves often viewed as proven, valid or
true.
6Advantages of combining quantitative and
qualitative results
- clarifying and answering more questions from
different perspectives - enhancing the validity of your findings
-
- increasing the capacity to cross check one data
set against another - Providing the detail of individual experiences
behind the statistics. - Helping in the development of particular
measures - Tracking stages over time.
7Philosophical integration of qualitative and
quantitative approaches
- Two current options
- Pragmatism
- seeks ways through the polarised
quantitative qualitative debate to find
practical solutions to the problem of differing
ideologies and methodologies recognising culture,
context, individual experience, the constructed
nature of reality, uncertainty, eclecticism,
pluralism and the need for creative innovation of
method. - The Transformative paradigm
- multiple realities are shaped by knowledge is
historically and socially situated - issues of power between researcher and researched
need to be explicitly addressed - the incorporation of qualitative and quantitative
methods are appropriate. - the transformative ethical orientation
comprises a strong human rights agenda
within notions of beneficence and social justice
8Conducting mixed methods research prior questions
- Is your research question one for which mixed
methods would be the best approach? - If so, which design would be the best?
- A mutual research design? involving acceptance
that the two approaches come from completely
different paradigms , celebrating their
differences and keeping them separate within the
design process the separate but together
position?. - Mixed methods?
- at which points will mixing occur? Design?
Analysis? Interpretation? - What sampling approaches will you utilise from
the probability and non-probabily suite? - How are you going to manage data analysis?
- quantitizing - converting qualitative data into
quantitative data or qualitizing - converting
quantitative data into qualitative data - To what degree will you qualitatively analyse
quantitative data and vice versa? - How are you going to display your results? -
Separately? Integrated? consolidated?
9Mixed method design
- Various forms of labeling and terminology have
been used for mixed method design synergy,
integration, triangulation, concurrent, parallel,
merging, concurrent, sequential, exploratory and
explanatory. Concurrent or sequential are the 2
main options -
- 1. Concurrent or parallel methods
- Here you would consider using multiple reference
points where separate data sets are collected at
the same time with the ultimate aim of merging
the two data sets either, - in a visual display such as a matrix
- by transforming the data (see quantitizing and
qualititzing data in crossover/mixed analyses
below) or - in the final discussion.
- Design might involve using dual sites with the
same sampling approach but with different data
(quantitative and qualitative) then using the
synthesised results to build up a complex
picture. -
10Design 2. Sequential explanatory/exploratory
- You could undertake a qualitative study to
explore a particular issue or phenomenon and
using an iterative approach you could create
hypotheses from these results which you could
test using a survey or experimental design. - Or, you could develop a short questionnaire
survey to elicit key issues which can then be
explained in depth using qualitative approaches
of interviewing and observation. Synthesis of the
two sets of results is needed to clarify the dual
outcomes and to utilise the increased validity
these two approaches provide.
11A typical sequencing design
- Stage 1 Representative survey of the population
- Stage 2 Exploratory qualitative interviews or
focus groups to tease out the findings of the
survey - Stage 3 Hypotheses generated from stages 1 and 2
are tested in various interventions which are
then evaluated - Stage 4 Participatory action research where the
participants take control of the development,
implementation and evaluation of the most
successful of these interventions.
12Issues to consider in attempting to combine data
sets
- You need to be familiar with both quantitative
and qualitative approaches - Mixing of paradigms, data collection, analysis
and interpretation, takes time and skills to do
well - Combined designs are more expensive than single
designs - Are there benefits to converting qualitative to
quantitative data?
13Crossover/mixed analysis
- Suggestions
- reduce dimensionality of either data set
(quantifying to basics) - integrate data display (visual presentation of
both sets as one) - transform data (Qual to quantb(numerical codes)
and quant to qual (themes) for analysis) - correlate data (correlate results from
quantitizing and qualitizing) - consolidate data (merging multiple data sets to
create new codes, variables etc) - compare data (compare findings)
- integrate data (into one or two sets of data)
- use warrented assertion analysis (seeking
meta-inferences from both sets) - import data (using follow-up findings from
qualitative to inform quantitative analysis and
vice versa)
14Presentation of dual results
- Separate data sets
- Requires a very large results section and
requires regular summaries of data findings which
will need to culminate in a final drawing
together of the findings so that the reader can
make sense of the diversity presented. -
- Combined data sets
- Amalgamate the findings in such a way that a neat
display of graphical information occurs, followed
by a few carefully chosen qualitative quotes to
display the homogeneity (or diversity) of the
data gathered. Matrixes can bring together
variables, themes and cases as can lists,
network diagrams and graphical displays. - Multiple data sets
- Currently the majority of data collected is still
within the survey/interview/observation/document
analysis framework with the documents
traditionally being written communications
displayed in a variety of creative ways.