Overdispersion Diagnostics for Generalized Linear Models
作者:
Diane Lambert,
Kathryn Roeder,
期刊:
Journal of the American Statistical Association
(Taylor Available online 1995)
卷期:
Volume 90,
issue 432
页码: 1225-1236
ISSN:0162-1459
年代: 1995
DOI:10.1080/01621459.1995.10476627
出版商: Taylor & Francis Group
关键词: Mixture;Random coefficient;Residuals;Score tests;Variance inflation
数据来源: Taylor
摘要:
Generalized linear models (GLM's) are simple, convenient models for count data, but they assume that the variance is a specified function of the mean. Although overdispersed GLM's allow more flexible mean-variance relationships, they are often not as simple to interpret nor as easy to fit as standard GLM's. This article introduces a convexity plot, orCplot for short, that detects overdispersion and relative variance curves and relative variance tests that help to understand the nature of the overdispersion. Convexity plots sometimes detect overdispersion better than score tests, and relative variance curves and tests sometimes distinguish the source of the overdispersion better than score tests.
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