Journal ArticleDOI
Additive hazards regression for case-cohort studies
Michal Kulich,Danyu Lin +1 more
TLDR
In this article, the authors used case-cohort data to estimate the regression parameter of the additive hazards model, which specifies that the conditional hazard function given a set of covariates is the sum of an arbitrary baseline hazard function and a regression function of the covariates.Abstract:
SUMMARY The case-cohort design is a common means of reducing cost in large epidemiological cohort studies. Under this design, covariates are measured only on the cases and a subcohort randomly selected from the entire cohort. In this paper, we demonstrate how to use the case-cohort data to estimate the regression parameter of the additive hazards model, which specifies that the conditional hazard function given a set of covariates is the sum of an arbitrary baseline hazard function and a regression function of the covariates. The proposed estimator is shown to be consistent and asymptotically normal with an easily estimated variance. The subcohort may be selected by independent Bernoulli sampling with arbitrary selection probabilities or by stratified simple random sampling. The efficiencies of various sampling schemes are investigated both analytically and by simulation. A real example is provided.read more
Citations
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Journal ArticleDOI
Exposure stratified case-cohort designs.
TL;DR: A variant of the case-cohort design is proposed for the situation in which a correlate of the exposure (or prognostic factor) of interest is available for all cohort members, and exposure information is to be collected for a case- cohort sample.
Journal ArticleDOI
Improving the Efficiency of Relative-Risk Estimation in Case-Cohort Studies
Michal Kulich,Danyu Lin +1 more
TL;DR: A class of weighted estimators with general time-varying weights that are related to a class of estimators proposed by Robins, Rotnitzky, and Zhao are developed and shown to be consistent and asymptotically normal under appropriate conditions.
Journal ArticleDOI
Weighted Likelihood for Semiparametric Models and Two-phase Stratified Samples, with Application to Cox Regression.
N. E. Breslow,Jon A. Wellner +1 more
TL;DR: A limit theorem for estimators of a general, possibly infinite dimensional parameter based on unbiased estimating equations containing estimated nuisance parameters is state and proved.
Journal ArticleDOI
Testing the proportional hazards assumption in case-cohort analysis.
Xiaonan Xue,Xianhong Xie,Marc J. Gunter,Thomas E. Rohan,Sylvia Wassertheil-Smoller,Gloria Y.F. Ho,Dominic J. Cirillo,Herbert Yu,Howard D. Strickler +8 more
TL;DR: Application of the proposed correlation tests to the example case-cohort investigation dataset showed that the Cox proportional hazards assumption was not satisfied for certain exposure variables in that study, an issue addressed through use of available, alternative analytical approaches.
Journal ArticleDOI
Stratified Case-Cohort Analysis of General Cohort Sampling Designs
TL;DR: In this article, the Chen approach is extended to accommodate stratified designs with surrogate variables available for all cohort members, such as stratified case-cohort and counter-matching designs.
References
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Book
Analysis of Survival Data
David Cox,D. Oakes +1 more
TL;DR: In this article, the authors give a concise account of the analysis of survival data, focusing on new theory on the relationship between survival factors and identified explanatory variables and conclude with bibliographic notes and further results that can be used for student exercises.
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TL;DR: In this article, the authors define the Ball Sigma-Field and Measurability of Suprema and show that it is possible to achieve convergence almost surely and in probability.
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Weak Convergence and Empirical Processes
TL;DR: This chapter discusses Convergence: Weak, Almost Uniform, and in Probability, which focuses on the part of Convergence of the Donsker Property which is concerned with Uniformity and Metrization.
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A generalization of sampling without replacement from a finite universe.
D. G. Horvitz,D. J. Thompson +1 more
TL;DR: In this paper, two sampling schemes are discussed in connection with the problem of determining optimum selection probabilities according to the information available in a supplementary variable, which is a general technique for the treatment of samples drawn without replacement from finite universes when unequal selection probabilities are used.
Journal ArticleDOI
Cox's Regression Model for Counting Processes: A Large Sample Study
TL;DR: In this article, the Cox regression model for censored survival data is extended to a model where covariate processes have a proportional effect on the intensity process of a multivariate counting process, allowing for complicated censoring patterns and time dependent covariates.