This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 360
Type: Contributed
Date/Time: Tuesday, August 3, 2010 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #306737
Title: Fixed vs. Mixed Parameterization in Logistic Regression: Application to Meta-Analysis
Author(s): Chin-Fang Weng*+
Companies: University of Maryland
Address: 7117 Edgevale Street, Chevy Chase, MD, 20815,
Keywords: GLMM ; conditional logistic ; random effects

Fixed intercept GLM, random intercept GLMM, and conditional logistic regression (clogit) are compared in a meta-analysis of 43 studies assessing the effect of diet on cancer incidence in rats. We also perform simulation studies to assess distributional behavior of regression estimates and tests of fit. Other simulations assess the effects of model misspecification, and increasing the sample size, either by adding additional studies or by increasing the sizes of a fixed number of studies. Estimates of fixed effects seem insensitive to increasing the sample sizes, but the deviance test of fit is biased. Conditional logistic regression avoids the possibility of bias when the number of studies is very large in a GLM analysis and also avoids effects of misspecification of the random effect distribution in a GLMM analysis, but at the cost of some information loss.

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