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Indexes and Scales

Indexes and Scales. Why use a “composite” measure of a concept? There is often no clear “single” indicator Increase the range of variation Make data analysis more “efficient”. Indexes vs. Sclaes. Index Simply “add up” single indicators to form a composite measure

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Indexes and Scales

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  1. Indexes and Scales • Why use a “composite” measure of a concept? • There is often no clear “single” indicator • Increase the range of variation • Make data analysis more “efficient”

  2. Indexes vs. Sclaes • Index • Simply “add up” single indicators to form a composite measure • Most common in social science • Scale • Assign score to pattern of responses (not all items are equal) • Commonality: rank order composite measures

  3. Index Construction • Item selection • Face validity • Unidimensionality • General/specific • Variance considerations • Scoring • Variance versus “adequate number of cases” in categories • Equal weight or not for the items in a composite index? • Empirical examinations • Bivariate versus multivariate • Dealing with missing data • Index validation

  4. Scales/Scaling • Empirically driven • Responses can be scaled, not survey items/questions • Reflect “intensity” of particular items • Is there a pattern in how the items tap a concept? • “easy and hard” questions

  5. Scale Construction • Key = not all indicators are equal • “intensity structures” among indicators • Better assurance of “ordinality” • Examples • Bogardus Social Distance Scale • Thurstone Scale • LikertScale • Semantic Differential • Guttman Scale

  6. Typologies • Allows a researcher to summarize the overlap/intersection of two or more variables • Typically driven by some combination of theory and data • life-course criminality • probation officer example • Difficult to use a typology as the dependent variable • Why do particular people fall into a particular typology (predicting typologies).

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