Inference And Application Of Two Pseudo-Likelihood-Based Methods For Case-Cohort Design Under Cox's Model

In many large cohort studies,the major cost typically arises from the measurement of primary exposure variables.With a limited budget,the researchers need to find a cost-effective design to address this problem.The case-cohort design is such a biased sampling scheme.The principle idea of this design is to obtain the measurements of expensive exposure variables only on a subset of the entire cohort and all the subjects outside the subcohort who experience the event of interest.In this paper,we discuss how to fit the Cox model to case-cohort data.We introduce two inferential methodologies which are based on pseudo-likelihood ideas and research their asymptotic properties.We conduct a series of simulations to assess the finite-sample performance of the proposed estimators and apply the proposed methods to real data analysis to demonstrate the application value in practice.First,we summarize two inference methods based on pseudo-likelihood theory and their asymptotic theory proposed by Prentice(1986)[24] and Chen & Lo(1999)[8].Then,we study and evaluate the performance of the above two estimation methods under a limited sample size through a series of statistical simulations.To study the practicability and effectiveness of case-cohort design as a reasonable alternative to traditional simple random sampling.Finally,we analyze an actual case-cohort data on nephroblastoma research,and demonstrate the practical application value of case-cohort design.The structure of this paper is as follows:In the first chapter,the research background of this paper is introduced,the development status of research direction is summarized,the sampling design of the model is introduced,and the main work and innovations of this paper are put forward.In the second chapter,a pseudo-likelihood inference method proposed by Prentice(1986)[24] for case-cohort design is studied.In the third chapter,an improved pseudo-likelihood inference method proposed by Chen and lo(1999)[8] is studied.In the fourth chapter,the application of two pseudo-likelihood inference methods in Cox model is studied.An application program is written to evaluate the performance of the above two methods under limited sample size through statistical model.In the fifth chapter,The research method was applied to analyze a cohort of actual cases of nephroblastoma.In the sixth chapter,The main work of this paper is summarized and the future research work is prospected.