Develops large-sample theory for survival analysis, suggesting improved methods for sequential data.
For the proportional hazards model of survival analysis, an appropriate large-sample theory is developed for cases of staggered entry and sequential analysis. The principal techniques involve an approximation of the score process by a suitable martingale and a random rescaling of time based on the observed Fisher information. As a result we show that the score process of the partial likelihood and the maximum partial likelihood estimator behave asymptotically like Brownian motion.
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Sellke et al. (1983) studied this question.
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