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2012 A note on conditional Akaike information for Poisson regression with random effects
Heng Lian
Electron. J. Statist. 6(none): 1-9 (2012). DOI: 10.1214/12-EJS665

Abstract

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

Information

Published: 2012
First available in Project Euclid: 5 January 2012

zbMATH: 1334.62140
MathSciNet: MR2879670
Digital Object Identifier: 10.1214/12-EJS665

Subjects:
Primary: 62J12

Rights: Copyright © 2012 The Institute of Mathematical Statistics and the Bernoulli Society

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