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Using the EM-algorithm for survival data with incomplete categorical covariates

✍ Scribed by Stuart R. Lipsitz; Joseph G. Ibrahim

Publisher
Springer
Year
1996
Tongue
English
Weight
507 KB
Volume
2
Category
Article
ISSN
1380-7870

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✦ Synopsis

Incomplete covariate data is a common occurrence in many studies in which the outcome is survival time. With generalized linear models, when the missing covariates are categorical, a useful technique for obtaining parameter estimates is the EM by the method of weights proposed in Ibrahim (1990). In this article, we extend the EM by the method of weights to survival outcomes whose distributions may not fall in the class of generalized linear models. This method requires the estimation of the parameters of the distribution of the covariates. We present a clinical trials example with five covariates, four of which have some missing values.

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