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Colloquium - 22 Oct 1998

Department of Statistics
Texas A&M University

ABSTRACT: We propose a method to handle non-randomly missing binary outcomes when the outcome variable is a bivariate vector of binary indicators. This problem is motivated from a stroke study where one of the objectives is to estimate the prevalence of functionally impaired among stroke patients. The proposed method consists of fitting four separate binary regression models: (i) for the baseline outcome; (ii) for the outcome at two years after the onset of the first stroke; (iii) for the product of these two; and (iv) for the missingness indicator. A jackknife variance estimate is proposed for the variance of the resulting estimates. The proposed analysis can be implemented in widely used software such as SAS.

Refreshments will be served in the Blocker Building, Room 447, at 3:30 p.m.

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