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


METHODS
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).


RESULTS
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.


CONCLUSIONS
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.
Atlanta Veterans Affairs Medical Center, Decatur, Georgia, United States of America.
Christopher
C
Rentsch
Infectious Disease Clinical Research Program, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America.
Ionut
I
Bebu
Atlanta Veterans Affairs Medical Center, Decatur, Georgia, United States of America ; Emory University School of Medicine, Atlanta, Georgia, United States of America ; Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America.
Jodie L
JL
Guest
Atlanta Veterans Affairs Medical Center, Decatur, Georgia, United States of America ; Emory University School of Medicine, Atlanta, Georgia, United States of America.
David
D
Rimland
Infectious Disease Clinical Research Program, Uniformed Services University of the Health Sciences, Bethesda, Maryland, United States of America.
Brian K
BK
Agan
Atlanta Veterans Affairs Medical Center, Decatur, Georgia, United States of America ; Emory University School of Medicine, Atlanta, Georgia, United States of America ; Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America.
Vincent
V
Marconi
D023241:Antiretroviral Therapy, Highly Active; D001499:Bayes Theorem; D015331:Cohort Studies; D003627:Data Interpretation, Statistical; D005260:Female; D015658:HIV Infections / Q000188:drug therapy / Q000401:mortality*; D006801:Humans; D053208:Kaplan-Meier Estimate; D008297:Male; D015999:Multivariate Analysis; D016016:Proportional Hazards Models