48 CB. Seaman qualitative analysis are sometimes boring,
often tedious, and always more time-consuming than expected. It is tempting to take shortcuts in the analysis process, but rigorous analysis is necessary for
the integrity of the research, and results in more insightful, useful, and valid conclusions.
As
in quantitative studies, data analysis should be planned upfront, before data collection begins. However, the difference is that qualitative researchers collect and analyse
data nearly in parallel, or at least alternate between the two. Qualitative analysis begins as soon as some significant amount of data has been collected. Preliminary analysis results also can modify subsequent data collection.
In the next two sections, we present
several analysis techniques, roughly divided into two categories, although the line between them is not well delineated. The first set of methods (Sect. 3.1) is used to generate hypotheses that fit the data (or
are grounded in the data, normally used in exploratory, or grounded theory
studies Glaser and Strauss, 1967). Section 3.2 describes some methods used to buildup the weight of evidence necessary to confirm hypotheses in confirmatory studies. Following, in Sect. 3.3, we discuss the use of visualization
of qualitative data, which is useful in conjunction with any analysis approach, and for presenting results. Finally, Sect. 3.4 presents some basic techniques for transforming qualitative data for subsequent quantitative analysis. The methods presented in these sections represent only
a small sample of the methods, techniques, and approaches available for analysing qualitative data. Yin (1994) and Miles and Huberman (1994) are excellent sources for other data analysis approaches.
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