Abstract
ABSTRACT The maximum likelihood approach to the proportional hazards model is considered. The purpose is to find a general approach to the analysis of the proportional hazards model, whether the baseline distribution is absolutely continuous, discrete, or a mixture. The advantage is that ties are treated without pain, while the performance for continuous data is almost the same as Cox's partial likelihood. The potential disadvantage with many nuisance parameters is taken care of by profiling them out for risk sets containing only one failure.
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