Developing an Analysis Plan in Content Analysis

Developing a plan for an analysis is the final planning step. It finks the data back to the evaluation question.

Traditionally, most content analyses have focused on the presence of variables or their frequency, intensity, or identity by space or time.

1. The Presence of a Variable

Analysis sometimes focuses on the mere presence of a variable in a document. For example, in examining the roles and performance of women in the military, GAO evaluators conducted a number of focus groups and treated the transcript for each group as a document. One v;:μ-iable was “attitude about women’s job performance,” and it had two categories, positive and negative. In one part of the analysis, the evaluators simply tabulated the number of focus groups in which participants registered either positive or negative views about women’s job performance. That is, a given focus group was described not by the number of positive and negative views that that group expressed but just by whether it expressed any positive or negative views.

2. The Frequency of a Category

Counting the number of times a category is coded is more than simply tabulating the number of documents in which the code appears. In a study of how federal employees view the government as a place to work, GAO evaluators identified 21 variables, each with two categories. For example, one variable was attitude about pay. with two categories: positive and negative. The evaluators gathered answers to an open-ended question at the end of a mail-out questionnaire sent to a random sample of employees; they counted all instances in which each category was coded across all documents. (GAO, 1992b) Singleton
et al. (1988) says that the frequency count is the most common method for measuring content.

3. Intensity

Analysis of intensity assumes ordinal categories. (GAO, 1992e) We often measure the intensity of a person’s opinions or attitudes, but other kinds of intensity variables are possible. For example, in one study, coders rated the strength of association between learning outcomes and 228 different factors in 179 reviews of school learning research. Strength of association had three categories: (1) weak, uncertain, or inconsistent relationship to learning, (2) moderate relationship, and (3) strong relationship. The primary data analysis was the computation of means for groups of variables. (Wang, Haertel, and Walberg, 1990).

4. Space or Time

Analyzing the space or time devoted to a topic in a document is common in content analysis. For example, the newspaper space (measured in column inches) associated with a topic may reflect the importance of a topic. For television or radio, air time is a similar measure. Note that using space or time in content analysis requires more than just coding the topic. For example, in one study, evaluators first used column inches to draw conclusions about newspaper coverage of foreign news and then applied a statistical test to compare differences in coverage between newspapers that had overseas staff with those that did not. (Budd, Thorp, and Donohew, 1967,pp. 12-13)

5. Analysis Options

In developing a data analysis plan, evaluators depend for analysis options on the measurement level of the variables-nominal, ordinal, or interval (or ratio). (GAO, 1992e) When evaluators choose nominal variables, they commonly tabulate category frequencies, but other possibilities exist. (Reynolds, 1984) With ordinal variables come other possibilities. (Hildebrand, Laing, and Rosenthal, 1977) Interval, or ratio, variables-which may be used in conjunction with variables coded from qualitative information-afford many possibilities for data analysis and are well covered in many statistical textbooks. (Moore and McCabe, 1989).

Source: GAO (2013), Content Analysis: A Methodology for Structuring and Analyzing Written Material: PEMD-10.3.1, BiblioGov.