Supporting information may be found in the online version of this article.
Penalized likelihood estimation for semiparametric mixed models, with application to alcohol treatment research†
Article first published online: 26 JUL 2012
Copyright © 2012 John Wiley & Sons, Ltd.
Statistics in Medicine
Volume 32, Issue 2, pages 335–346, 30 January 2013
How to Cite
Chen, J., Liu, L., Johnson, B. A. and O'Quigley, J. (2013), Penalized likelihood estimation for semiparametric mixed models, with application to alcohol treatment research. Statist. Med., 32: 335–346. doi: 10.1002/sim.5528
- Issue published online: 17 DEC 2012
- Article first published online: 26 JUL 2012
- Manuscript Accepted: 11 MAY 2012
- Manuscript Received: 17 NOV 2011
- NIAAA. Grant Number: RC1 AA019274
- AHRQ. Grant Number: R01 HS020263
- generalized linear mixed models (GLMMs);
- Laplace approximation;
- logistic models;
- longitudinal data analysis;
- non-normal random effects
In this article, we implement a practical computational method for various semiparametric mixed effects models, estimating nonlinear functions by penalized splines. We approximate the integration of the penalized likelihood with respect to random effects with the use of adaptive Gaussian quadrature, which we can conveniently implement in SAS procedure NLMIXED. We carry out the selection of smoothing parameters through approximated generalized cross-validation scores. Our method has two advantages: (1) the estimation is more accurate than the current available quasi-likelihood method for sparse data, for example, binary data; and (2) it can be used in fitting more sophisticated models. We show the performance of our approach in simulation studies with longitudinal outcomes from three settings: binary, normal data after Box–Cox transformation, and count data with log-Gamma random effects. We also develop an estimation method for a longitudinal two-part nonparametric random effects model and apply it to analyze repeated measures of semicontinuous daily drinking records in a randomized controlled trial of topiramate. Copyright © 2012 John Wiley & Sons, Ltd.