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

Abstract Details

Activity Number: 251
Type: Contributed
Date/Time: Monday, August 2, 2010 : 2:00 PM to 3:50 PM
Sponsor: International Biometric Society
Abstract - #307249
Title: Improving the Performance of the Generalized Score Tests in Longitudinal Studies with Missing Data
Author(s): Kumar B. Rajan*+ and Carlos F. Mendes de Leon
Companies: Rush Institute for Healthy Aging and Rush Institute for Healthy Aging
Address: 1645 W Jackson Blvd , Chicago , IL, 60612,
Keywords: Generalized Score Test ; Missing Data ; Robust Wald Test ; Weighted Estimating Equations
Abstract:

The robust Wald test, the (quasi) likelihood ratio test, and the generalized score test are three widely used test statistics in regression models, when no assumption is made about the missing data. However, these test statistics have not been well studied under different missing mechanisms. The robust Wald test based on weighted estimating equations can be used as a test statistic, when the data are missing at random. We propose a weighted generalized score test that performances better in terms of power and nominal Type-I error probabilities, under missing at random assumption. We will derive the asymptotic distribution of this test statistic and compare the performance of this test statistic in finite sample simulation studies. The usefulness of the proposed method is illustrated using a study aimed at investigating the risk factors associated with disabilities among aging adults.


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