VARIABLE SELECTION FOR ESTIMATING THE OPTIMAL TREATMENT REGIMES IN THE PRESENCE OF A LARGE NUMBER OF COVARIATES

doi:10.1214/18-AOAS1154

CORC > 上海财经大学 > 上海财经大学

	VARIABLE SELECTION FOR ESTIMATING THE OPTIMAL TREATMENT REGIMES IN THE PRESENCE OF A LARGE NUMBER OF COVARIATES
	Zhang, Baqun 1; Zhang, Min 2
刊名	ANNALS OF APPLIED STATISTICS
	2018-12
卷号	12 期号:4 页码:2335-2358
关键词	C-learning classification high-dimensional data misclassification error personalized medicine dynamic treatment regime variable selection
ISSN号	1932-6157
DOI	10.1214/18-AOAS1154
英文摘要	Most existing methods for optimal treatment regimes, with few exceptions, focus on estimation and are not designed for variable selection with the objective of optimizing treatment decisions. In clinical trials and observational studies, often numerous baseline variables are collected and variable selection is essential for deriving reliable optimal treatment regimes. Although many variable selection methods exist, they mostly focus on selecting variables that are important for prediction (predictive variables) instead of variables that have a qualitative interaction with treatment (prescriptive variables) and hence are important for making treatment decisions. We propose a variable selection method within a general classification framework to select prescriptive variables and estimate the optimal treatment regime simultaneously. In this framework, an optimal treatment regime is equivalently defined as the one that minimizes a weighted misclassification error rate and the proposed method forward sequentially select prescriptive variables by minimizing this weighted misclassification error. A main advantage of this method is that it specifically targets selection of prescriptive variables and in the meantime is able to exploit predictive variables to improve performance. The method can be applied to both single- and multiple-decision point setting. The performance of the proposed method is evaluated by simulation studies and application to a clinical trial.
WOS研究方向	Mathematics
语种	英语
出版者	INST MATHEMATICAL STATISTICS
WOS记录号	WOS:000450015900013
内容类型	期刊论文
源URL	[http://10.2.47.112/handle/2XS4QKH4/448]
专题	上海财经大学
通讯作者	Zhang, Min
作者单位	1.Shanghai Univ Finance & Econ, Sch Stat & Management, Shanghai, Peoples R China; 2.Univ Michigan, Dept Biostat, Ann Arbor, MI 48109 USA
推荐引用方式 GB/T 7714	Zhang, Baqun,Zhang, Min. VARIABLE SELECTION FOR ESTIMATING THE OPTIMAL TREATMENT REGIMES IN THE PRESENCE OF A LARGE NUMBER OF COVARIATES[J]. ANNALS OF APPLIED STATISTICS,2018,12(4):2335-2358.
APA	Zhang, Baqun,&Zhang, Min.(2018).VARIABLE SELECTION FOR ESTIMATING THE OPTIMAL TREATMENT REGIMES IN THE PRESENCE OF A LARGE NUMBER OF COVARIATES.ANNALS OF APPLIED STATISTICS,12(4),2335-2358.
MLA	Zhang, Baqun,et al."VARIABLE SELECTION FOR ESTIMATING THE OPTIMAL TREATMENT REGIMES IN THE PRESENCE OF A LARGE NUMBER OF COVARIATES".ANNALS OF APPLIED STATISTICS 12.4(2018):2335-2358.