JSM 2004 Online Program

Abstract #301835

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Activity Number:	415
Type:	Contributed
Date/Time:	Thursday, August 12, 2004 : 8:30 AM to 10:20 AM
Sponsor:	Biometrics Section
Abstract - #301835
Title:	Multiple Imputation in Microarray Data Analysis
Author(s):	John Barnard*+ and Xuejun Peng and Yaomin Xu
Companies:	Cleveland Clinic Foundation and Cleveland Clinic Foundation and Cleveland Clinic Foundation
Address:	9500 Euclid Ave./wb4, Cleveland, OH, 44195,
Keywords:	multiple inputation ; microarray ; missing data
Abstract:	Various reasons may cause incomplete data in microarray analysis and these may lead to Missing Complete at Random, Missing at Random, or Missing not at Random. This makes it necessary to apply different missing data imputation methods accordingly. We discuss in this paper how we choose imputation methods and how we evaluate the "goodness" of specific methods. Simulations and real data application are used to demonstrate how well these multiple imputation methods are able to restore complete data and how they affect downstream statistical inference.

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