JSM 2004 - Toronto

Abstract #301759

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Activity Number: 177
Type: Topic Contributed
Date/Time: Tuesday, August 10, 2004 : 8:30 AM to 10:20 AM
Sponsor: Section on Health Policy Statistics
Abstract - #301759
Title: Causal Inference for Morbidity Outcomes in the Presence of Death
Author(s): Brian L. Egleston*+ and Daniel O. Scharfstein and Ellen Freeman and Sheila West
Companies: Johns Hopkins University and Johns Hopkins University and Johns Hopkins University and Johns Hopkins University
Address: Dept. of Biostatistics/Johns Hopkins Public Health, Baltimore, MD, 21205-2179,
Keywords: causal inference ; competing risk ; sensitivity analysis ; visual impairment
Abstract:

Evaluation of the causal effect of an exposure on a morbidity outcome is often complicated by the presence of death as a competing risk. In this setting, the causal effect is only well-defined for the principal stratum of subjects who would live whatever be the exposure. Motivated by aging researchers interested in understanding the causal effect of visual impairment on depression in a population with a high mortality rate, we introduce a set of scientifically driven assumptions to identify the causal effect among those who would live both with and without visual impairment. To evaluate the robustness of our analysis to nonidentifiable assumptions, we propose a method for performing a sensitivity analysis. We apply our method using the first three rounds of survey data from the Salisbury Eye Evaluation, a population-based cohort study of 2,520 older adults.

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