Choosing and Interpreting a Metric for Data Analysis

Abstract

The article examines the role that the scale of the criterion variable plays in the development and interpretation of univariate models. The discussion begins by reviewing several exploratory data analysis techniques that use relationships between spread and location parameters to suggest power transformations of the criterion vanable. Data from a study of pretrial release illustrate the techniques. An examination of residuals is shown to complement the search for a good transformation. The effect that independent or carrier variables have on untransformed criterion variables is examinedfor power, logit, and arcsin transformations of the criterion variable. The discussion shows how various transformations imply different relationships between criterion and carrier variables. Inverse transformations are bnefly discussed.