Social Research Methods: Qualitative and Quantitative Approaches

ANALYSIS OF QUALITATIVE DATA

FIGURE 2 Theory, Surface Reality, and
Underlying Structures

Theory

about Reality

Visible

Surface

Reality

Unseen

below Surface

Underlying
Social Reality

Structure

Structure

Structure

Structure

Researcher’s

Observations

Often we cannot directly observe features of
the social world. We cannot observe a deep loving
relationship between two people. We can see its out-
ward manifestation only in a kiss, specific deeds of
affection, and acts of kindness. Likewise, we can-
not directly observe a social structure such as social
class. Nonetheless, we see its outward signs in dif-
ferences in how people act, their career assump-
tions, their material possessions, and so forth.
Sometimes we are misled by outward observation.
We analyze data for both the surface level of reality
and the deeper structures and forces that may lie
unseen beneath the surface.

ANALYTIC STRATEGIES FOR
QUALITATIVE DATA

Most qualitative researchers use techniques of cod-
ing, memo writing, and looking for outcroppings
to some degree. This section introduces you to
seven strategies you can use to analyze qualitative
data: (1) ideal type, (2) successive approximation,
(3) illustrative method, (4) domain analysis, (5) ana-
lytic comparison, (6) narrative analysis, and (7) neg-
ative case method.
As stated earlier in this chapter, strategies for
qualitative data are more diverse, less standardized,

and less explicit than in quantitative research. As

Mahoney (1999:1192–1193) noted, “The absence

of methodological explicitness has made it difficult

for many readers to fully understand and appreciate

the arguments of [qualitative data] researchers.”

Some researchers use only one strategy whereas

others combine several.

In general,data analysismeans a search for pat-

terns in data—recurrent behaviors, objects, phases,

or ideas. Once you identify a pattern, you need to

interpret it in terms of a social theory or the setting

in which it occurred. This allows you to move from

the particular description of a historical event or

social setting to a more general interpretation.

Data take many forms in qualitative research.

For example, field research data include raw sense

data that a researcher experiences, recorded data

in field notes, and selected or processed data that

appear in a final report (see Figure 3). Data analy-

sis involves examining, sorting, categorizing, eval-

uating, comparing, synthesizing, and contemplating

the coded data as well as reviewing the raw and

recorded data.

Ideal Types

One of the most common strategies of qualitative

data analysis is Max Weber’s ideal type. It is a model

or mental abstraction of social relations or pro-

cesses. Ideal types are pure standards against which

the data or “reality” can be compared. An ideal type

is an artificial device used for comparison because

no reality ever fits an ideal type. For example,

I develop a mental model of the ideal democracy or

an ideal college beer party. These abstractions with

lists of characteristics do not describe any specific

democracy or beer party; nevertheless, they are use-

ful when applied to many specific cases to see how

well each case measures up to the ideal.

Weber’s method of ideal types also comple-

ments Mills’ method of agreement (see analytic

comparison). The method of agreement focuses

attention on what is common across cases and

looks for common causes in cases with a common

outcome. By itself, the method of agreement

implies a comparison against actual cases. This

comparison of cases could also be made against an

idealized model. You could develop an ideal type of