This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 458
Type: Topic Contributed
Date/Time: Wednesday, August 4, 2010 : 8:30 AM to 10:20 AM
Sponsor: ENAR
Abstract - #307273
Title: Variable Selection for Panel Count Data via Nonconcave Penalized Estimating Function
Author(s): Xin He*+ and Xingwei Tong and Liuquan Sun and Jianguo Sun
Companies: University of Maryland and Beijing Normal University and Chinese Academy of Sciences and University of Missouri
Address: 2234H SPH Building, College Park, MD, 20742,
Keywords: estimating function ; non-concave penalized procedure ; oracle procedure ; panel count data ; variable selection

Panel count data often occur in long-term studies that concern occurrence rate of a recurrent event, and their analysis has recently attracted a great deal of attention. However, there does not seem to exist any established approach for variable selection with respect to panel count data. For the problem, we adopt the idea behind the non-concave penalized likelihood approach and develop a non-concave penalized estimating function approach. The proposed methodology selects variables and estimates regression coefficients simultaneously, and an algorithm is presented for this process. We show that the proposed procedure performs as well as the oracle procedure in that it yields the estimates as if the correct submodel were known. Simulation studies are conducted for assessing the performance of the proposed approach. An illustrative example from a cancer study is provided.

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