Social Research Methods: Qualitative and Quantitative Approaches

ANALYSIS OF QUALITATIVE DATA

us to use statistical procedures. Qualitative analy-
sis requires more effort to read and reread data
notes, reflect on what is read, and make compar-
isons based on logic and judgment.
Most forms of qualitative data analysis involve
coding and writing analytic memos. Both are labor-
intensive and time-intensive efforts. They require
reading data carefully and thinking about them

seriously. In addition, the chapter presented

methods we used for the analysis of qualitative data.

The techniques presented in this chapter are only a

sample of the full range of qualitative data analysis

techniques. The chapter discussed also the impor-

tance of thinking about negative evidence and

events that are not present in the data.

KEY TERMS

analytic comparison
analytic domain
axial coding
cultural domain
domain analysis
empty boxes
event structure analysis (ESA)
folk domain

historical contingency

illustrative method

method of agreement

method of difference

mixed domain

narrative analysis

negative case method

open coding

outcropping

path dependency

periodization

qualitative comparative

analysis (QCA)

selective coding

successive approximation

REVIEW QUESTIONS

1.Identify four differences between quantitative and qualitative data analysis.

2.How does the process of conceptualization differ for qualitative and quantitative

research?

3.How does data coding differ in quantitative and qualitative research, and what are

the three types of coding used by a qualitative researcher?

4.What is the purpose of analytic memo writing in qualitative data analysis?

5.Describe successive approximation.

6.What are the empty boxesin the illustrative method, and how are they used?

7.What is the difference between the method of agreement and the method of dif-

ference? Can a researcher use both together? Explain why or why not.

8.What are the parts of a domain, and how are they used in domain analysis?

9.What are the major features of a narrative?

10.Why is it important to look for negative evidence, or things that do not appear in
the data, for a full analysis?

NOTES

1. See Miles and Huberman (1994) and Ragin (1987).
   These should not be confused with statistical techniques
   for “qualitative” data (see Haberman, 1978). These are
   sophisticated statistical techniques (e.g., logit and log

linear) for quantitative variables in which the data are at

nominal or ordinal levels. They are better labeled as tech-

niques for categorical data.