首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Estimation using penalized quasilikelihood and quasi-pseudo-likelihood in Poisson mixed models
Authors:Xihong Lin
Institution:(1) Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA
Abstract:We consider two estimation schemes based on penalized quasilikelihood and quasi-pseudo-likelihood in Poisson mixed models. The asymptotic bias in regression coefficients and variance components estimated by penalized quasilikelihood (PQL) is studied for small values of the variance components. We show the PQL estimators of both regression coefficients and variance components in Poisson mixed models have a smaller order of bias compared to those for binomial data. Unbiased estimating equations based on quasi-pseudo-likelihood are proposed and are shown to yield consistent estimators under some regularity conditions. The finite sample performance of these two methods is compared through a simulation study.
Keywords:Asymptotic bias  Estimating equations  Generalized linear mixed models  Laplace expansion  Overdispersion  Variance components
本文献已被 PubMed SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号