文章基本信息

标题：A Spatially-adjusted Bayesian Additive Regression Tree Model to Merge Two Datasets
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作者：Song Zhang ; Ya-Chen Tina Shih ; Peter Muller 等
期刊名称：Bayesian Analysis
印刷版ISSN：1931-6690
电子版ISSN：1936-0975
出版年度：2007
卷号：2
期号：3
页码：611-634
出版社：International Society for Bayesian Analysis
摘要：Scientic hypotheses of interest often involve variables that are not available in a single survey. This is a common problem for researchers working with survey data. We propose a model-based approach to provide information about the missing variable. We use a spatial extension of the BART (Bayesian additive regression tree) model. The imputation of the missing variables and infer- ence about the relationship between two variables are obtained simultaneously as posterior inference under the proposed model. The uncertainty due to imputation is automatically accounted for. A simulation analysis and an application to data on self-perceived health status and income are presented.
关键词：BART, CART, Missing variables, Spatial model, Survey