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存在不依从与对照组接受治疗时比例风险模型中的治疗效应估计AI 解读

Summary Methods for adjusting for non-compliance and contamination, which respect the randomization, are extended from binary outcomes to time-to-event analyses by using a proportional hazards model. A simple non-iterative method is developed when there are no covariates, which is a generalization of the Mantel–Haenszel estimator. More generally, a ‘partial likelihood’ is developed which accommodates covariates under the assumption that they are independent of compliance. A…

Cox 回归中的迭代残差与时变协变量效应AI 解读

Summary The Cox proportional hazards model, which is widely used for the analysis of treatment and prognostic effects with censored survival data, makes the assumption that the hazard ratio is constant over time. Nonparametric estimators have been developed for an extended model in which the hazard ratio is allowed to change over time. Estimators based on residuals are appealing as they are easy to use and relate in a simple way to the more restricted Cox model estimator.…

回顾性匹配下调整后的 Nelson–Aalen 估计AI 解读

In certain situations, randomized trials are not possible, but formal comparison of survival in two or more groups is still desirable. Although no substitute for randomization, application of the matched case-control design to survival studies may minimize the potential bias. Comparable estimates for each treatment group can be obtained by matching or stratifying according to prognostic variables, and weighting each individual to make stratum distributions the same over the…

Cox 回归的若干新估计量AI 解读

New estimators for Cox regression are considered. Their asymptotic properties, both on and off the model, are established. Corollaries include conditions under which the maximum partial likelihood estimator defines a parameter in the population and the asymptotics of the case-cohort estimator. Robust estimators that minimize the asymptotic variance subject to a bound on the maximal bias on infinitesimal neighborhoods are discussed. The estimators are illustrated with medical…

Cox 模型的最大加权偏似然估计AI 解读

New estimators for Cox regression that maximize a weighted version of the partial likelihood are considered. Their asymptotic properties on the model are sketched. Estimators with bounded influence curves are identified and shown to have good asymptotic relative efficiency. The results of a small simulation study are included. The estimators are applied to a well-known data set. The possible influence of an outlying observation on the Cox estimator can be of any magnitude.…

嵌套回归模型族中条件风险比的信息界AI 解读

SUMMARY Information bounds are obtained for a parametric treatment effect in a nested family of models for the conditional distribution of survival given confounding variables. The family extends from the fully parametric Weibull model to a completely nonparametric model for right-censored data and includes the Cox model and the stratified version of it. It is shown that, in certain special cases, there is no loss of information about the treatment effect when going from a…