Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/98306
Title: A note on conditional Akaike information for Poisson regression with random effects
Authors: Lian, Heng
Issue Date: 2012
Source: Lian, H. (2012). A note on conditional Akaike information for Poisson regression with random effects. Electronic Journal of Statistics, 6(0), 1-9.
Series/Report no.: Electronic journal of statistics
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 infer- ence 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.
URI: https://hdl.handle.net/10356/98306
http://hdl.handle.net/10220/13261
ISSN: 1935-7524
DOI: http://dx.doi.org/10.1214/12-EJS665
Fulltext Permission: none
Fulltext Availability: No Fulltext
Appears in Collections:SPMS Journal Articles

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