When good confidence intervals go bad: predictor sort experiments and ANOVA

Abstract

A predictor sort experiment is one in which experimental units are allocated on the basis of the values of a predictor variable that is correlated with the response. Standard ANOVA analyses of predictor sort experiments can lead to confidence intervals whose actual coverages are poor matches to nominal coverages. Correct coverages can be obtained by adjusting confidence interval lengths by appropriate factors, or by performing analyses of covariance.

Citation

Verrill, Steve. 1999. When good confidence intervals go bad: predictor sort experiments and ANOVA. The American Statistician. 53(1): 38-42.