Please use this identifier to cite or link to this item: https://doi.org/10.1080/03610910802361366
Title: An empirical study of statistical properties of variance partition coefficients for multi-level logistic regression models
Authors: Li, J. 
Gray, B.R.
Bates, D.M.
Keywords: Empirical distribution
Laplacian approximation
Multi-level logistic models
Variance partition coefficients
Issue Date: Nov-2008
Citation: Li, J., Gray, B.R., Bates, D.M. (2008-11). An empirical study of statistical properties of variance partition coefficients for multi-level logistic regression models. Communications in Statistics: Simulation and Computation 37 (10) : 2010-2026. ScholarBank@NUS Repository. https://doi.org/10.1080/03610910802361366
Abstract: Partitioning the variance of a response by design levels is challenging for binomial and other discrete outcomes. Goldstein (2003) proposed four definitions for variance partitioning coefficients (VPC) under a two-level logistic regression model. In this study, we explicitly derived formulae for multi-level logistic regression model and subsequently studied the distributional properties of the calculated VPCs. Using simulations and a vegetation dataset, we demonstrated associations between different VPC definitions, the importance of methods for estimating VPCs (by comparing VPC obtained using Laplace and penalized quasilikehood methods), and bivariate dependence between VPCs calculated at different levels. Such an empirical study lends an immediate support to wider applications of VPC in scientific data analysis.
Source Title: Communications in Statistics: Simulation and Computation
URI: http://scholarbank.nus.edu.sg/handle/10635/104996
ISSN: 03610918
DOI: 10.1080/03610910802361366
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