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
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.
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