Fitting a mixture distribution to complex censored survival data using generalized linear models

A. J. Scallan

Journal of Applied Statistics, 1999, vol. 26, issue 6, 747-753

Abstract: Mixture models may arise for a variety of reasons in survival data analysis. This paper shows how such models that involve potentially complex cross-classification by covariates may be easily fitted using a package such as GLIM. The method employs an auxiliary Poisson-binomial model in order to find the maximum-likelihood estimates of the model parameters, and has been implemented using GLIM macros.

Date: 1999
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DOI: 10.1080/02664769922188

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