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 Scale
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 Scoring Empirical examinations
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 Examples
“intensity structures” among indicators
Better assurance of “ordinality”
Examples
Bogardus Social Distance Scale
Thurstone Scale
LIkert Scale
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).

7. SPSS: Creating an Index
From web site
Download assignment (.doc file) and read
This will include a description of the data file
Download the SPSS data file (.sav file) and use to do assignment