学术报告
阅读次数:731

题目:A Generalized Partially Linear Mean-covariance Regression Model for Longitudinal Proportional Data, with Applications to the Analysis of Quality of Life Data from Cancer Clinical Trials

报告人:郑雪莹 讲师(复旦大学)

地点:瑞安楼609室

时间:2017年12月13日(星期三)14:30-15:30

报告摘要

Motivated by the analysis of quality of life data from a clinical trial on early breast cancer, we propose in this generalized partially linear mean-covariance regression model for longitudinal proportional data, which are bounded in a closed interval. Cholesky decomposition of the covariance matrix for within-subject responses and generalized estimation equations are used to estimate unknown parameters and the nonlinear function in the model. Simulation studies are performed to evaluate the performance of the proposed estimation procedures. Our new model is also applied to analyze the data from the cancer clinical trial that motivated this research. In comparison with available models in the literature, the proposed model does not require specific parametric assumptions on the density function of the longitudinal responses and the probability function of the boundary values and can capture dynamic changes of time or other interested variables on both mean and covariance of the correlated proportional responses.

个人简介

郑雪莹,讲师,复旦大学公共卫生学院生物统计老师,毕业于香港大学统计与精算系,师从著名统计学家Wing-Kam Fung教授,主持国家自然科学基金青年项目,发表多篇高水平SCI期刊论文。

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