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区间删失失效时间数据的病例队列研究AI 解读

The case-cohort design has been widely used as a means of cost reduction in assembling or measuring expensive covariates in large cohort studies. The existing literature on the case-cohort design is mainly focused on right-censored data. In practice, however, the failure time is often subject to interval-censoring; it is known only to fall within some random time interval. In this paper, we consider the case-cohort study design for interval-censored failure time and develop…

事件类别缺失时复发事件均值函数的非参数估计AI 解读

Recurrent event data frequently arise in longitudinal studies when study subjects possibly experience more than one event during the observation period. Often, such recurrent events can be categorized. However, part of the categorization may be missing due to technical difficulties. If the event types are missing completely at random, then a complete case analysis may provide consistent estimates of regression parameters in certain regression models, but estimates of the…

病例—队列研究的更高效估计量AI 解读

The case-cohort study design, used to reduce costs in large cohort studies, is a random sample of the entire cohort, named the subcohort, augmented with subjects having the disease of interest but not in the subcohort sample. When several diseases are of interest, several case-cohort studies may be conducted using the same subcohort, with each disease analyzed separately, ignoring the additional exposure measurements collected on subjects with the other diseases. This is not…

存在信息性终止事件的重复事件半参数加性率模型AI 解读

We propose a semiparametric additive rate model for modelling recurrent events in the presence of a terminal event. The dependence between recurrent events and terminal event is nonparametric. A general transformation model is used to model the terminal event. We construct an estimating equation for parameter estimation and derive the asymptotic distributions of the proposed estimators. Simulation studies demonstrate that the proposed inference procedure performs well in…

多疾病结局病例队列研究的边际风险率模型AI 解读

Case-cohort study designs are widely used to reduce the cost of large cohort studies while achieving the same goals, especially when the disease rate is low. A key advantage of the case-cohort study design is its capacity to use the same subcohort for several diseases or for several subtypes of disease. In order to compare the effect of a risk factor on different types of diseases, times to different events need to be modelled simultaneously. Valid statistical methods that…

基于相关失效时间数据的风险比参数估计方程AI 解读

Weighted partial likelihood estimating equations are proposed for the estimation of marginal hazard ratio parameters based on correlated failure time data. Asymptotic distribution theory is derived for the solution to such equations using martingale convergence results and inverse function theory. Simulation studies and theoretical efficiency calculations indicate that the inclusion of weights in the estimating equation produces important efficiency gains only if the…

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删失多元失效时间数据的协方差与生存函数估计AI 解读

The covariance between counting process martingales is used to characterize the dependence between two failure time variates. A representation of the bivariate survivor function is obtained in terms of the marginal survivor functions and this covariance function. A closely related representation expresses the bivariate survivor function in terms of marginal survivor functions and a conditional covariance function, leading to a new nonparametric survivor function estimator.…

删失多元失效时间数据的协方差与生存函数估计AI 解读

The covariance between counting process martingales is used to characterize the dependence between two failure time variates. A representation of the bivariate survivor function is obtained in terms of the marginal survivor functions and this covariance function. A closely related representation expresses the bivariate survivor function in terms of marginal survivor functions and a conditional covariance function, leading to a new nonparametric survivor function estimator.…