JSM 2004 Online Program

Abstract #301962

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Activity Number:	435
Type:	Contributed
Date/Time:	Thursday, August 12, 2004 : 10:30 AM to 12:20 PM
Sponsor:	SSC
Abstract - #301962
Title:	Efficient Estimation in Regression Analysis with Missing Data in Two-phase Studies
Author(s):	Yang Zhao*+ and Jerald F. Lawless and Donald L. McLeish
Companies:	University of Waterloo and University of Waterloo and University of Waterloo
Address:	Dept. of Statistics and Actuarial Science, Waterloo, ON, N2L 3G1 , Canada
Keywords:	two-phase study ; missing data ; semiparametric maximum likelihood estimator
Abstract:	Regression analysis that involves incomplete observations can utilize auxiliary information to provide more efficient estimates of regression parameters. We recommend an efficient EM algorithm that can be used to estimate the parameters in regression models with some covariates missing at random. The advantages of this method in dealing with continuous missing variables with fine surrogates are discussed. Extensive simulation studies to compare it with other available method will be provided.

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