OVERDISPERSION DIAGNOSTICS FOR GENERALIZED LINEAR-MODELS

Generalized linear models (GLM's) are simple, convenient models for co unt data, but they assume that the variance is a specified function of the mean. Although overdispersed GLM's allow more flexible mean-varia nce relationships, they are often not as simple to interpret nor as ea sy to fit as standard GLM's. This article introduces a convexity plot, or C plot for short, that detects overdispersion and relative varianc e curves and relative variance tests that help to understand the natur e of the overdispersion. Convexity plots sometimes detect overdispersi on better than score tests, and relative variance curves and tests som etimes distinguish the source of the overdispersion better than score tests.