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Creating Codes in Content Analysis

Codes are simply abbreviations, or tags, for segments of text. Before evaluators can code a document, they must first create a code for each variable’s categories. To minimize error, a code should be an abbreviated version of a category. In figure 4.1, for example, the variable is “attitude toward cost-sharing,” and it has three

18
Aug
Coding Options in Content Analysis

Textual material can be coded directly on the computer or it can be coded manually and transferred clerically to electronic media. With the latter option, a coder works with hard-copy documents and simply marks the passages with a pencil or colored marker. Training requirements are minimal.2 Some content analysis software programs make it relatively

18
Aug
Coder Selection and Training in Content Analysis

Coding is generally quicker and more accurate and credible the more expertise coders have in the subject of the material being analyzed. For example, in coding documents pertaining to Medicare claims, the coder’s knowledge of medical terminology and practices would probably be useful. Coders are trained to accurately apply the codes in training sessions

18
Aug
The Potential for Coding Error in Content Analysis

The four interrelated potential sources of coding inaccuracy in most applications of content analysis are (1) deficiencies in the documents, (2) ambiguity in the judgment process, (3) coder bias, and (4) coder error. (Orwin, 1994) For example, a poorly written document may lead to a coder’s making ambiguous decisions, or ambiguity in the judgment

18
Aug
Selecting and Managing Documents in Content Analysis

1. Using All the Documents Even though the population of documents may seem conceptually clear, assembling them for coding generally has three problems: missing documents, inappropriate documents, and uncodable documents. There may be a discrepancy between the supposed population of documents and those actually located. For example, in an evaluation of international development projects

18
Aug
Applying Codes in Content Analysis

In manual coding on hard-copy documents, the coder simply marks the boundaries of the recording unit and writes the code in the margin of the document, as in figure 4.1. It is often helpful and speedier to use different colored pens for each variable. The procedure is similar when using a computer, but the

18
Aug
Using a Computer to Code in Content Analysis

This section assumes that the documents to be coded are available in a word processing format such as WordPerfect and that coding proceeds with the computer program called Textbase Alpha. Textbase Alpha was designed for the analysis of qualitative data, but it was not specifically oriented toward traditional content analysis. However, it is simple

18
Aug
Preparing for Data Analysis in Content Analysis

The basic analytic task in content analysis is to count the occurrence of codes, whether all occurrences of a given category (for example, all occurrences of Stars and Stripes articles that portray a negative image of the military) or only certain subcategories of occurrences (for example, Separate counts of such articles in the Pacific

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Aug
Estimating Reliability of Content Analysis

When several coders code the documents, then- consistency is important. If the coders differ substantially, then the results of the content analysis become questionable. Chapter 4 outlined steps for minimizing unreliability. Another important step is to assign selected documents to several coders at once so that estimates of reliability can be made (see appendix

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18
Aug
Counting a Code’s Frequency in Content Analysis

Drawing inferences from the frequency of codes is the simplest and often the most useful form of data analysis. Drawing conclusions in the Stars and Stripes assignment, evaluators counted the number of articles that presented a negative image of the military and compared the number to the number of wire service articles with negative

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Aug
Reporting the Methodology and Results of Content Analysis

The methodology and results of a content analysis should be reported the way they are for other evaluations. The methodology should be described in sufficient detail that readers will have a clear understanding of how the work was carried out and its strengths and limitations. For example, the report should reveal the evaluation question

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Aug
Planning the Content Analysis

1. Be Clear About the Questions The evaluation questions drive the study. If they are Questions ambiguous or not suited to the users’ needs, even a well-implemented method will produce findings of doubtful value. To be clear about the questions means to state them as specifically as possible so that the answers will be useful

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18
Aug
Coding in Content Analysis

1. Produce a Coding Manual A good coding manual is indispensable. AvoSrf the temptation to save time by not producing one or by producing only the skeleton of one. The time spent in being complete will be more than repaid by making the coders’ task easier and faster and, especially, by ensuring coding of

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Aug
Analyzing and Reporting the Data in Content Analysis

1. Cross-Check Preliminary Results Things are not always what they seem. Try to verify findings by using related variables or slightly different analysis methods. This is also a time to check on the reliability of the coding process. 2. Apply Statistical Tests In some circumstances, statistical tests of significance may be appropriate. Use them

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Aug
Analysis of Qualitative Data in Content Analysis

Content analysis applies to textual information in the form of words. An analyst can classify text into categories as described in chapter 1. The categories are treated like numerical data in subsequent statistical manipulations. The statistical analysis permits the analyst to draw conclusions about the information in the text. This is the traditional form

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Aug
Software for Content Analysis

This appendix describes computer software that may be useful to content analysis. The list of programs here is by no means complete, and it is purely descriptive, not a GAO endorsement of any program. The descriptions focus on features of the software that are necessary or optional for use in content analysis; they do

18
Aug
Intercoder Reliability in Content Analysis

An important measure forjudging the quality of a content analysis is the extent to which the results can be reproduced. Known as intercoder reliability, this measure indicates how well two or more coders reached the same judgments in coding the data. Among the variety of methods that have been proposed for estimating intercoder reliability,

18
Aug
The questionnaire in the survey process

The questionnaire represents one part of the survey process. It is, however, a very vital part of the process. A poorly written questionnaire will not provide the data that are required or, worse, will provide data that are incorrect. The first task with any survey is to define the objectives that the study is

20
Aug
Stakeholders in the questionnaire

Clearly there are a number of different stakeholders in the questionnaire, on each of whom the way in which it is written and laid out will have an effect. There can be up to five different groups of people who have an inter­est in the questionnaire, and each one has a different requirement of

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Aug
The objectives of the study relating to the questionnaire

1. Relating research objectives to business objectives The brief that the researcher receives may sometimes include the business objectives for the study and the research objectives required to achieve them. For example: Business objective: to enter the mobile telecoms market with a pricing package that is attractive to at least 60 per cent of

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Aug
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