This paper discusses the nested case-control analysis under a class of general additive-multiplicative hazard models which includes the Cox model and the additive hazard model as special cases.A pseudo-score is constr...This paper discusses the nested case-control analysis under a class of general additive-multiplicative hazard models which includes the Cox model and the additive hazard model as special cases.A pseudo-score is constructed to estimate the regression parameters.The resulting estimator is shown to be consistent and asymptotically normally distributed.The limiting variance-covariance matrix can be consistently estimated by the nested case-control data.A simulation study is conducted to assess the finite sample performance of the proposed estimator and a real example is provided for illustration.展开更多
Case-cohort design usually requires the disease rate to be low in large cohort study,although it has been extensively used in practice.However,the disease with high rate is frequently observed in many clinical studies...Case-cohort design usually requires the disease rate to be low in large cohort study,although it has been extensively used in practice.However,the disease with high rate is frequently observed in many clinical studies.Under such circumstances,it is desirable to consider a generalized case-cohort design,where only a fraction of cases are sampled.In this article,we propose the inference procedure for the additive hazards regression under the generalized case-cohort sampling.Asymptotic properties of the proposed estimators for the regression coefcients are established.To demonstrate the efectiveness of the generalized case-cohort sampling,we compare it with simple random sampling in terms of asymptotic relative efciency.Furthermore,we derive the optimal allocation of the subsamples for the proposed design.The fnite sample performance of the proposed method is evaluated through simulation studies.展开更多
The case-cohort design is widely used in large epidemiological studms and prevention trials for cost reduction. In such a design, covariates are assembled only for a subcohort which is a random subset of the entire co...The case-cohort design is widely used in large epidemiological studms and prevention trials for cost reduction. In such a design, covariates are assembled only for a subcohort which is a random subset of the entire cohort and any additional cases outside the subcohort. In this paper, we discuss the case-cohort analysis with a class of general additive-multiplicative hazard models which includes the commonly used Cox model and additive hazard model as special cases. Two sampling schemes for the subcohort, Bernoulli sampling with arbitrary selection probabilities and stratified simple random sampling with fixed subcohort sizes, are discussed. In each setting, an estimating function is constructed to estimate the regression parameters. The resulting estimator is shown to be consistent and asymptotically normally distributed. The limiting variance-covariance matrix can be consistently estimated by the case-cohort data. A simulation study is conducted to assess the finite sample performances of the proposed method and a real example is provided.展开更多
基金Supported by the National Natural Science Foundation of China(10971033,11101091)
文摘This paper discusses the nested case-control analysis under a class of general additive-multiplicative hazard models which includes the Cox model and the additive hazard model as special cases.A pseudo-score is constructed to estimate the regression parameters.The resulting estimator is shown to be consistent and asymptotically normally distributed.The limiting variance-covariance matrix can be consistently estimated by the nested case-control data.A simulation study is conducted to assess the finite sample performance of the proposed estimator and a real example is provided for illustration.
基金supported by the Fundamental Research Fund for the Central Universitiessupported by National Natural Science Foundation of China(Grant No.11301545)supported by National Natural Science Foundation of China(Grant No.11171263)
文摘Case-cohort design usually requires the disease rate to be low in large cohort study,although it has been extensively used in practice.However,the disease with high rate is frequently observed in many clinical studies.Under such circumstances,it is desirable to consider a generalized case-cohort design,where only a fraction of cases are sampled.In this article,we propose the inference procedure for the additive hazards regression under the generalized case-cohort sampling.Asymptotic properties of the proposed estimators for the regression coefcients are established.To demonstrate the efectiveness of the generalized case-cohort sampling,we compare it with simple random sampling in terms of asymptotic relative efciency.Furthermore,we derive the optimal allocation of the subsamples for the proposed design.The fnite sample performance of the proposed method is evaluated through simulation studies.
基金supported by the National Natural Science Foundation of China(11101091)the Specialized Research Fund for the Doctoral Program of Higher Education of China(20110071120023)supported by the National Natural Science Foundation of China(10971033)
文摘The case-cohort design is widely used in large epidemiological studms and prevention trials for cost reduction. In such a design, covariates are assembled only for a subcohort which is a random subset of the entire cohort and any additional cases outside the subcohort. In this paper, we discuss the case-cohort analysis with a class of general additive-multiplicative hazard models which includes the commonly used Cox model and additive hazard model as special cases. Two sampling schemes for the subcohort, Bernoulli sampling with arbitrary selection probabilities and stratified simple random sampling with fixed subcohort sizes, are discussed. In each setting, an estimating function is constructed to estimate the regression parameters. The resulting estimator is shown to be consistent and asymptotically normally distributed. The limiting variance-covariance matrix can be consistently estimated by the case-cohort data. A simulation study is conducted to assess the finite sample performances of the proposed method and a real example is provided.
