Abstract #300694

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JSM 2003 Abstract #300694
Activity Number: 239
Type: Contributed
Date/Time: Tuesday, August 5, 2003 : 10:30 AM to 12:20 PM
Sponsor: Section on Statistics & the Environment
Abstract - #300694
Title: Modeling Random Effects for Multilevel Generalized Linear Models
Author(s): Junfeng Liu*+ and Dipak K. Dey
Companies: University of Connecticut and University of Connecticut
Address: Department of Statistics, Storrs Mansfield, CT, 06269-0001,
Keywords: generalized linear models ; missing data ; multilevel ; skew multivariate distribution ; random effects
Abstract:

This paper considers skew modeling random effects for multilevel generalized linear models using a Bayesian approach. The random effects are modeled using multivariate normal, as well as multivariate skew normal and skew student's t distributions. Logit and probit link functions are considered for the multilevel binomial regression model. The methodology is exemplified through a data on teratogenic of the two niacin analogs. Simulation based methods are used for model fitting and comparison. Next a log linear multilevel Poisson model is considered for a count data on diurnal activity of the Baltic sea peracardis with ignorable missing covariates. The proposed models are validated through several model diagnostics.

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