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To help you with the analysis of qualitative data, it is useful
to produce an interview summary form or a focus group
summary form which you complete as soon as possible
after each interview or focus group has taken place. This
includes practical details about the time and place, the
participants, the duration of the interview or focus group,
and details about the content and emerging themes. It is useful to complete these forms as
soon as possible after the interview and attach them to
your transcripts. The forms help to remind you about
the contact and are useful when you come to analyse
the data.
There are many different types of qualitative data analysis.
The method you use will depend on your research topic,
your personal preferences and the time, equipment and finances
available to you. Also, qualitative data analysis is a
very personal process, with few rigid rules and procedures.
Formats for analysis
However, to be able to analyse your data you must first of
all produce it in a format that can be easily analysed. This
might be a transcript from an interview or focus group, a
series of written answers on an open-ended questionnaire,
or field notes or memos written by the researcher. It is
useful to write memos and notes as soon as you begin
to collect data as these help to focus your mind and alert
you to significant points which may be coming from the
data. These memos and notes can be analysed along with
your transcripts or questionnaires.
You can think of the different types of qualitative data
analysis as positioned on a continuum. At the
one end are the highly qualitative, reflective types of analysis,
whereas on the other end are those which treat the
qualitative data in a quantitative way, by counting and
coding data.
For those at the highly qualitative end of the continuum,
data analysis tends to be an on-going process, taking place
throughout the data collection process. The researcher
thinks about and reflects upon the emerging themes, adapting
and changing the methods if required. For example, a
researcher might conduct three interviews using an interview
schedule she has developed beforehand. However,
during the three interviews she finds that the participants
are raising issues that she has not thought about previously.
So she refines her interview schedule to include
these issues for the next few interviews. This is data analysis.
She has thought about what has been said, analysed the
words and refined her schedule accordingly.
Thematic analysis
When data is analysed by theme, it is called thematic analysis.
This type of analysis is highly inductive, that is, the
themes emerge from the data and are not imposed upon it
by the researcher. In this type of analysis, the data collection
and analysis take place simultaneously. Even background
reading can form part of the analysis process,
especially if it can help to explain an emerging theme.
Closely connected to thematic analysis is comparative analysis.
Using this method, data from different people is compared
and contrasted and the process continues until the
researcher is satisfied that no new issues are arising. Comparative
and thematic analyses are often used in the same
project, with the researcher moving backwards and forwards
between transcripts, memos, notes and the research
literature.
Content analysis
For those types of analyses at the other end of the qualitative
data continuum, the process is much more mechanical
with the analysis being left until the data has been
collected. Perhaps the most common method of doing this
is to code by content. This is called content analysis. Using
this method the researcher systematically works through
each transcript assigning codes, which may be numbers
or words, to specific characteristics within the text. The
researcher may already have a list of categories or she
may read through each transcript and let the categories
emerge from the data. Some researchers may adopt both
approaches. This type of analysis
can be used for open-ended questions which have been
added to questionnaires in large quantitative surveys, thus
enabling the researcher to quantify the answers.
Discourse analysis
Falling in the middle of the qualitative analysis continuum
is discourse analysis, which some researchers have named
conversational analysis, although others would argue that
the two are quite different. These methods look at patterns
of speech, such as how people talk about a particular subject,
what metaphors they use, how they take turns in conversation,
and so on. These analysts see speech as a
performance; it performs an action rather than describes
a specific state of affairs or specific state of mind. Much
of this analysis is intuitive and reflective, but it may also
involve some form of counting, such as counting instances
of turn-taking and their influence on the conversation and
the way in which people speak to others.
Processing the data
1. You need to think about the data from the moment you
start to collect the information.
2. You need to judge the value of your data, especially
that which may come from dubious sources.
3. As your research progresses you need to interpret the
data so that you, and others, can gain an understanding
of what is going on.
4. Finally, you need to undertake the mechanical process
of analysing the data.
It is possible to undertake the mechanical process using
computing software which can save you a lot of time,
although it may stop you becoming really familiar with
the data. There are many dedicated qualitative analysis
programs of various kinds available to social researchers
that can be used for a variety of different tasks. For example,
software could locate particular words or phrases;
make lists of words and put them into alphabetical order;
insert key words or comments; count occurrences of
words or phrases or attach numeric codes. Some software
will retrieve text, some will analyse text and some will help
to build theory. Although a computer can undertake these
mechanical processes, it cannot think about, judge or interpret
qualitative data
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