Controlling variable selection by the addition of pseudovariables

• 成果类型: Article
• 署名作者: Wu, Yujun; Boos, Dennis D.; Stefanski, Leonard A.
• 署名单位: Rutgers University System; Rutgers University New Brunswick; Rutgers University Biomedical & Health Sciences; North Carolina State University
• 刊物名称: JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
• ISSN/ISSBN: 0162-1459
• DOI: 10.1198/016214506000000843
• 发表日期: 2007
• 页码: 235-243
• 关键词: regression; MODEL; likelihood; criterion; bootstrap

摘要

We propose a new approach to variable selection designed to control the false selection rate (FSR), defined as the proportion of uninformative variables included in selected models. The method works by adding a known number of pseudovariables to the real dataset, running a variable selection procedure, and monitoring the proportion of pseudovariables falsely selected. Information obtained from bootstrap-like replications of this process is used to estimate the proportion of falsely selected real variables and to tune the selection procedure to control the FSR.