Combining epidemiologic and biostatistical tools to enhance variable selection in HIV cohort analyses.


Rentsch, C; Bebu, I; Guest, JL; Rimland, D; Agan, BK; Marconi, V; (2014) Combining epidemiologic and biostatistical tools to enhance variable selection in HIV cohort analyses. PLoS One, 9 (1). e87352. ISSN 1932-6203 DOI: https://doi.org/10.1371/journal.pone.0087352

[img] UNSPECIFIED - Published Version
License:

Download ([error in script])

Abstract

Variable selection is an important step in building a multivariate regression model for which several methods and statistical packages are available. A comprehensive approach for variable selection in complex multivariate regression analyses within HIV cohorts is explored by utilizing both epidemiological and biostatistical procedures. Three different methods for variable selection were illustrated in a study comparing survival time between subjects in the Department of Defense's National History Study and the Atlanta Veterans Affairs Medical Center's HIV Atlanta VA Cohort Study. The first two methods were stepwise selection procedures, based either on significance tests (Score test), or on information theory (Akaike Information Criterion), while the third method employed a Bayesian argument (Bayesian Model Averaging). All three methods resulted in a similar parsimonious survival model. Three of the covariates previously used in the multivariate model were not included in the final model suggested by the three approaches. When comparing the parsimonious model to the previously published model, there was evidence of less variance in the main survival estimates. The variable selection approaches considered in this study allowed building a model based on significance tests, on an information criterion, and on averaging models using their posterior probabilities. A parsimonious model that balanced these three approaches was found to provide a better fit than the previously reported model.

Item Type: Article
Faculty and Department: Faculty of Epidemiology and Population Health > Dept of Population Health (2012- )
Research Centre: Population Studies Group
PubMed ID: 24489902
Web of Science ID: 330570000136
URI: http://researchonline.lshtm.ac.uk/id/eprint/2550442

Statistics


Download activity - last 12 months
Downloads since deposit
0Downloads
38Hits
Accesses by country - last 12 months
Accesses by referrer - last 12 months
Impact and interest
Additional statistics for this record are available via IRStats2

Actions (login required)

Edit Item Edit Item