Semiparametric Inference for Data with a Continuous Outcome from Two-Phase Probability Sampling Scheme
主 题: Semiparametric Inference for Data with a Continuous Outcome from Two-Phase Probability Sampling Scheme
报告人: 许王莉教授（人民大学）
时 间: 2014-05-22 14:00-15:00
地 点: 理科一号楼1303会议室（统计中心活动）
Biased sampling schemes can be a cost effective way to enhance study efficiency. In this paper, we propose a new two-phase sampling design for a continuous outcome, the probability sampling scheme, in which, the second phase supplement samples are drawn based on a sampling probability calculated from the first phase data. The basic idea is to oversample those $X$ that are on the two tails of its distribution. A semiparametric empirical likelihood inference procedure is proposed and the asymptotic normality properties of the proposed estimator is developed. Simulation results indicate that the sampling scheme and the proposed estimator is more efficient and more powerful than the existing outcome dependent sampling design and the simple random sampling designs. We illustrate the proposed method with a data set from an environmental epidemiologic study, to assess the relationship between maternal polychlorinated biphenyl level and children\'s IQ test performance.
About the speaker
（报告人介绍）：2006年博士毕业于中国科公司数学与系统科学研究院应用所。现为中国人民大学统计公司副教授，硕士生导师，医学与生物统计教研室主任。研究兴趣：模型检验，纵向数据分析，抽样设计等。
