Abstract #301129

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JSM 2003 Abstract #301129
Activity Number: 203
Type: Contributed
Date/Time: Tuesday, August 5, 2003 : 8:30 AM to 10:20 AM
Sponsor: ENAR
Abstract - #301129
Title: Missing Data in a Small Longitudinal Study: A Comparison of Monotone, Propensity, or Nonmonotone Multiple Imputation Methods with Complete Case and General Linear Mixed Model Analyses
Author(s): Dawen Sui*+ and Rachel T. Fouladi
Companies: University of Texas M.D. Anderson Cancer Center and University of Texas M.D. Anderson Cancer Center
Address: Behavioral Science, Houston, TX, 77030-4009,
Keywords: mixed model ; missing data pattern ; repeated measures ; imputation method
Abstract:

This paper examines the relative performance of the different approaches to the treatment of missing data values in a small longitudinal study. In particular, we contrast results from the treatment of missing data using monotone, propensity, and nonmonotone multiple imputation methods with results from complete case and general linear mixed model analyses. The discussion will focus on the characteristics of the resultant model parameter estimates, their standard errors, and the rejection probabilities of the corresponding test statistic.

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