A note on conditional Akaike information for Poisson regression with random effects

作者：Lian Heng^*

来源：Electronic Journal of Statistics, 2012, 6: 1-9.

DOI：10.1214/12-EJS665

• Akaike information
• AIC
• model selection
• Poisson regression

A popular model selection approach for generalized linear mixed-effects models is the Akaike information criterion, or AIC. Among others, [7] pointed out the distinction between the marginal and conditional inference depending on the focus of research. The conditional AIC was derived for the linear mixed-effects model which was later generalized by [5]. We show that the similar strategy extends to Poisson regression with random effects, where conditional AIC can be obtained based on our observations. Simulation studies demonstrate the usage of the criterion.

• 出版日期2012
• 单位南阳理工学院