Electronic Journal of Statistics

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

Heng Lian

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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.

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Electron. J. Statist., Volume 6 (2012), 1-9.

First available in Project Euclid: 5 January 2012

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Primary: 62J12: Generalized linear models

Akaike information AIC model selection Poisson regression


Lian, Heng. A note on conditional Akaike information for Poisson regression with random effects. Electron. J. Statist. 6 (2012), 1--9. doi:10.1214/12-EJS665. https://projecteuclid.org/euclid.ejs/1325772677

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