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Why use composite measures?
The answer to this question requires a little foundation. Social scientists do research to establish valid, reliable relationships among concepts. These relationships form the basis of social science knowledge. Establishing a relationship between two concepts, however, depends on establishing an empirical relationship among the indicators used to represent the concepts. Establishing valid, reliable empirical relationships depends upon obtaining a valid, reliable, and precise measure for each indicator. Years of research experience have shown that composite measures generally provide the best way to get good measurements of indicators. We can use the exam illustration again to show how composite measures improve measurement of indicators. The 20 questions were selected by your instructor to measure your knowledge of the course material. Instead of 20 questions, would you want your grade to be based on one question: Pass or fail? You would certainly answer "No" to this question. Your instructor might ask the one question that you could not answer. You would much prefer having a number of questions. Increasing the number of questions provides a better measure of all the questions you were prepared to answer. This applies as well to the construction of measures of attitudes, beliefs, behavior, and other variables. Attitudes toward various religious, ethnic, racial, or other groups, for example, can range from extremely positive or highly negative. A single question or item seldom captures a person's attitude toward some group. Using a number of items, each of which probes a different aspect of relations with members of that group, gives a more valid and precise measure of where a person's attitude falls on the continuum from one extreme to another. Increasing the number of items also improves measurement by allowing for greater variability in the scores obtained. With additional items, scores will have a broader range, from favorable to unfavorable, for example, or from high to low numerically. Using the exam illustration again, scores on the exam could range from 0 to 20 instead of just from 0 to 1. Greater variability also improves measurement of validity and reliability. In the case of the exam, both you and your instructor have a more valid estimate of your knowledge based on 20 questions instead of just 1 question. The same is true for measurement of variables. Box 7.1 lists the advantages of using composite measures.
Composite measures aid in analysis of data in other ways. Your grade point average illustrates this advantage of composite measures. A grade point average or its equivalent is the mean (the sum of all grades divided by the number of grades) of all grades received so far. Each final grade for each course is the score for that course. Having the scores in numerical form allows your university to calculate and adjust grade point average as each new grade is added. Similarly, in social research composite measures can be used in a variety of statistical analyses, giving clearer and more powerful results. Scales Scales are used widely in social research, mainly to measure variables that vary greatly in degree or intensity. A few of the thousands of recent studies based on composite measures include: Alrareb's (1997) investigation of attitudes toward Muslims; Kridli's (1997) investigation of plans to use oral contraceptives; Fattah's (1981) study of husband-wife decision-making among Iraqi farm families; and the investigation by Hassan and colleagues (1988) of attitudes toward male/female equality. These studies were based on the use of scales, consisting of sets of statements with responses ranging from one extreme, such as "strongly agree" to the other extreme, such as "strongly disagree." This technique was developed by Renis Likert in the 1930s and is widely used in social research. |