JSM 2004 - Toronto

Abstract #300437

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Activity Number: 271
Type: Contributed
Date/Time: Tuesday, August 10, 2004 : 2:00 PM to 3:50 PM
Sponsor: General Methodology
Abstract - #300437
Title: Nonimputational Technique for Parameter Estimation on Missing Data
Author(s): Sergey S. Tarima*+ and Yuriy G. Dmitriev
Companies: University of Kentucky and Tomsk State University
Address: 817 Patterson Office Tower , Lexington, KY, 40506-0027,
Keywords: parameter estimation ; missing data ; nonimputational technique for missing data

In the paper a new nonimputational approach to parameter estimation on missing data is proposed. This approach combines parameters' estimates obtained from different parts of a sample defined by corresponded missing data patterns. Improvement of the suggested estimators achieved by involving the effect of mutual correlation between estimators derived from different parts of a sample. New estimators are asymptotically unbiased and provide asymptotically smaller variances. This approach is developed for the case of an ignorable missing data mechanism but it also can be applied for a some nonignorable missing data situations. Applying the suggested methodology to a dropout situation with missing completely at random a well-known Kaplan-Meier estimator is derived.

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