Abstract #300792

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JSM 2002 Abstract #300792
Activity Number: 384
Type: Contributed
Date/Time: Thursday, August 15, 2002 : 8:30 AM to 10:20 AM
Sponsor: General Methodology
Abstract - #300792
Title: Local Sensitivity to Nonignorability in Frequentist Inference
Author(s): Guoguang (Julie) Ma*+ and Daniel Heitjan
Affiliation(s): Merck & Company, Inc. and Columbia University
Address: BL3-2, Blue Bell, Pennsylvania, 19422,
Keywords: Frequentist Inference ; Missing data ; Sensitivity analysis
Abstract:

The problem of missing data is very common in biomedical research. When observations are nonignorably missing, standard inferences can give misleading results. In this paper, we develop a method for computing the sensitivity of frequentist data summaries to small departures from an ignorable model. Specifically, we use Taylor-series expansions to evaluate the local sensitivity of quantities such as the mean and variance of the distribution, the power of a test, and the coverage probability of a confidence interval. We illustrate the analysis by simulation studies and a real-world example.

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