Title: Assessing and Adjusting Nonresponse Bias in Small Area Estimation via Bayesian Hierarchical Spatial Models
Speaker: Prof. Chong Zhuoqiong He,University of Missouri, Columbia, USA
Date: 2015.3.20（Friday）10:00-11:00AM
Place: 维格堂113
Abstract：Nonresponse is a persistent problem in surveys because results from respondents only are subject to nonresponse bias. Many methods have been developed to deal with ignorable (missing at random) nonresponse data. In this paper, we provide a method to assess and adjust nonignorable (not missing at random) nonresponse bias in a small area estimation problem. We propose a bivariate Bayesian hierarchical linear mixed model to estimate both satisfaction rate and response rate. This model uses spatial dependencies among subdomains and auxiliary information from sample units to assess and adjust nonresponse bias. In addition, it explicitly includes a parameter that indicates whether the nonresponse is ignorable or not. The method is used to analyze the 2001 Missouri Deer Hunter Attitude Survey (MDHAS). The result shows that the nonresponse in MDHAS is nonignorable. Hunter age and the number of deer harvested have strong effects on satisfaction and response rates, and spatial dependencies are strong amongst counties of hunters‘ residences. The estimated satisfaction rates are lower after adjusting for nonresponse bias.
报告人简介：Chong Zhuoqiong He教授是美国密苏里大学哥伦比亚分校教授，主要研究贝叶斯分析、局部估计、生存分析、抽样调查、时空模型、最优实验设计等，尤其对流行病学、农业，生态，环保与节能等领域的应用统计方法有很深入的研究。
详见个人网页：//www.stat.missouri.edu/~chong/
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