Please use this identifier to cite or link to this item: https://doi.org/10.1002/sim.4233
Title: Parametric variable selection in generalized partially linear models with an application to assess condom use by HIV-infected patients
Authors: Leng, C. 
Liang, H.
Martinson, N.
Keywords: AIDS
Condom use
LASSO
Least squares approximation
Local linear regression
Profile likeli-hood
Quasilikelihood
SCAD
Sexual behavior
Spline smoothing
Issue Date: 20-Jul-2011
Citation: Leng, C., Liang, H., Martinson, N. (2011-07-20). Parametric variable selection in generalized partially linear models with an application to assess condom use by HIV-infected patients. Statistics in Medicine 30 (16) : 2015-2027. ScholarBank@NUS Repository. https://doi.org/10.1002/sim.4233
Abstract: To study significant predictors of condom use in HIV-infected adults, we propose the use of generalized partially linear models and develop a variable selection procedure incorporating a least squares approximation. Local polynomial regression and spline smoothing techniques are used to estimate the baseline nonparametric function. The asymptotic normality of the resulting estimate is established. We further demonstrate that, with the proper choice of the penalty functions and the regularization parameter, the resulting estimate performs as well as an oracle procedure. Finite sample performance of the proposed inference procedure is assessed by Monte Carlo simulation studies. An application to assess condom use by HIV-infected patients gains some interesting results, which cannot be obtained when an ordinary logistic model is used. © 2011 John Wiley & Sons, Ltd.
Source Title: Statistics in Medicine
URI: http://scholarbank.nus.edu.sg/handle/10635/105293
ISSN: 02776715
DOI: 10.1002/sim.4233
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