Please use this identifier to cite or link to this item: https://doi.org/10.1080/03610910802361366
DC FieldValue
dc.titleAn empirical study of statistical properties of variance partition coefficients for multi-level logistic regression models
dc.contributor.authorLi, J.
dc.contributor.authorGray, B.R.
dc.contributor.authorBates, D.M.
dc.date.accessioned2014-10-28T05:10:00Z
dc.date.available2014-10-28T05:10:00Z
dc.date.issued2008-11
dc.identifier.citationLi, 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
dc.identifier.issn03610918
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/104996
dc.description.abstractPartitioning 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.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1080/03610910802361366
dc.sourceScopus
dc.subjectEmpirical distribution
dc.subjectLaplacian approximation
dc.subjectMulti-level logistic models
dc.subjectVariance partition coefficients
dc.typeArticle
dc.contributor.departmentSTATISTICS & APPLIED PROBABILITY
dc.description.doi10.1080/03610910802361366
dc.description.sourcetitleCommunications in Statistics: Simulation and Computation
dc.description.volume37
dc.description.issue10
dc.description.page2010-2026
dc.identifier.isiut000260208500006
Appears in Collections:Staff Publications

Show simple item record
Files in This Item:
There are no files associated with this item.

SCOPUSTM   
Citations

8
checked on Dec 14, 2019

WEB OF SCIENCETM
Citations

7
checked on Nov 28, 2019

Page view(s)

80
checked on Dec 14, 2019

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.