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复杂抽样调查数据的 Cox 比例风险模型拟合AI 解读

Binder (1992) proposed a method of fitting Cox's proportional hazards to models to survey data with complex sampling designs. He defined the regression parameter of interest as the solution to the partial likelihood score equation based on all the data values of the survey population under study, and developed heuristically a procedure to estimate the regression parameter and the corresponding variance. In this paper, we provide a formal justification of Binder's method.…

右删失数据中连续事件间隔时间分布的非参数估计AI 解读

In many follow-up studies, each subject can potentially experience a series of events, which may be repetitions of essentially the same event or may be events of entirely different natures. This paper provides a simple nonparametric estimator for the multivariate distribution function of the gap times between successive events when the follow-up time is subject to right censoring. The estimator is consistent and, upon proper normalisation, converges weakly to a zero-mean…

计数过程的加速失效时间模型AI 解读

We present a natural extension of the conventional accelerated failure time model for survival data to formulate the effects of covariates on the mean function of the counting process for recurrent events. A class of consistent and asymptotically normal rank estimators is developed for estimating the regression parameters of the proposed model. In addition, a Nelson-Aalen-type estimator for the mean function of the counting process is constructed, which is consistent and,…

Current status data arise when the only knowledge about the failure time of interest is whether the failure occurs before or after a random monitoring time. We propose to analyse such data by the semiparametric additive hazards model, which specifies that the hazard function for the failure time associated with a set of possibly time-dependent covariates is the sum of an arbitrary baseline hazard function and a regression function of covariates. Under certain conditions on…

依赖删失下两个失效时间分布的比较AI 解读

In a randomised clinical trial to compare two groups of patients, suppose that the time to disease occurrence, the major response variable, may be subject to dependent censoring by death or selective patient withdrawal, while the patients who have reached the disease endpoint are followed for their secondary endpoints or survival information. To adjust for the dependent censoring in assessing the group difference in disease occurrence, we assume that, on a logarithmic scale,…