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Activity Number: 517
Type: Topic Contributed
Date/Time: Wednesday, August 7, 2013 : 10:30 AM to 12:20 PM
Sponsor: Committee on Statistics and Disability
Abstract - #309044
Title: Restricted Fence Method for Covariate Selection in Longitudinal Data Analysis
Author(s): Thuan Nguyen*+ and Jiming Jiang
Companies: Oregon Health and Science University and University of California, Davis
Keywords: Longitudinal model selection ; Restricted fence method ; Robust boostrapping

Fence method (Jiang et al. 2008) is a recently proposed strategy for model selection. It was motivated by the limitation of the traditional information criteria in selecting parsimonious models in some nonconventional situations, such as mixed model selection. Jiang, Nguyen & Rao (2009) simplified the adaptive fence method of Jiang et al. (2008) to make it more suitable and convenient to use in a wide variety of problems. Still, the current modification encounters computational difficulties when applied to high dimensional and complex problems. To address this concern, we proposed a restricted fence procedure that combines the idea of fence with that of the restricted maximum likelihood (REML). Furthermore, we propose a robust bootstrap procedure to choose adaptively the tuning parameter used in the restricted fence. We focus on problems of longitudinal studies, and demonstrate the performance of the new procedure, and its comparison with the information criteria in a simulation study. The method is further illustrated by a real-data analysis.

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