MAXIMUM-LIKELIHOOD-ESTIMATION AND TESTING OF A POISSON REGRESSION-MODEL

被引：0
|
作者：
WAN, JY
GALECKI, AT
机构：
[1] UNIV MICHIGAN,DEPT GERIATR RES,ANN ARBOR,MI 48109
[2] UNIV MICHIGAN,CTR TRAINING,ANN ARBOR,MI 48109
来源：
METHODS OF INFORMATION IN MEDICINE | 1992年 / 31卷 / 03期
关键词：
DEVIANCE; EXPONENTIAL REGRESSION; INCIDENCE RATE; POISSON REGRESSION;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
A Poisson regression model is proposed for the analysis of incidence rates presented in a two-way table classified by two categorical variables. It is shown that the likelihood function is the same as that using Glasser's exponential covariate model. An algorithm is given to solve the maximum likelihood estimates of the regression parameters. The model is evaluated via deviance and the method is illustrated with an example. Some extensions of the model are discussed.
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页码：215 / 218
页数：4
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