Stings in the Tails: Detecting and Dealing with Censored Data

Abstract

Variables often show evidence of clustering at extreme values and of graininess, that is, of a limited number of distinct values. Scores on two subscales of a quality-of-life measure, traditionally analyzed with OLS regression or ANOVA models, provide examples. Ignoring or failing to detect such features of the data will result in poor estimates of effect size.