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Development of composite scores from a set of responses is another form of data modification. The responses to items are the initial, raw data. These data are analyzed to get composite scores, which generate data for a new variable. Information about the new variable is then added to the codebook. After that, analysis proceeds either by hand tallying or the new date are entered into a computer for analysis. Combining responses to items is a frequent form of data modification. Sometimes there are relatively few responses in the extreme attributes for variables. To illustrate, suppose you got the following responses to an item stating that women have the same right to enter political life as men:
Compared to the middle attributes, there are relatively few frequencies for "strongly agree" and "strongly disagree." In situations like this, the best choice is to collapse or combine the attribute with few frequencies with the one immediately above or below it. In this case, we would combine "strongly agree" and "agree" and make it one attribute and then do the same for "disagree" and "strongly disagree." We would also update our codebook with these changes. Collapsing attributes, however, results in throwing away a portion of the measurement of a variable and, therefore, should be done with some caution. Anytime you combine data, you should update your codebook so that you have an accurate map to your data. This will include giving new codes to the responses and may require entering new data in the database before beginning analysis. With the data coded, you are ready to begin analysis. Whether you do this by hand or with the help of a computer program, analysis begins with the examination of each variable, taken one at a time. This is the focus of the next chapter. Aids Internet resources In contrast to other topics, we found only a few web sites dealing with data preparation as would be done by an individual researcher working by him or her self. We suggest you visit the one site we found. This site should help you organize your data for analysis. Data Preparation describes and illustrates steps involved with data preparation, includes keeping track of the data, checking data for accuracy and completeness, developing a database structure, entering data into a computer, and modifying data during the process of analysis In addition, most of the sites for computer-based systems listed earlier in this chapter also include instructions for preparing and entering data for these systems. Many of these instructions can be applied to the process of data preparation and computer entry in general. |