Variable selection for random effects two-part models

doi:10.1177/0962280218784712

CSpace > 应用数学研究所

	Variable selection for random effects two-part models
	Han, Dongxiao 1; Liu, Lei 2; Su, Xiaogang 3; Johnson, Bankole 4; Sun, Liuquan1
	2019-09-01
发表期刊	STATISTICAL METHODS IN MEDICAL RESEARCH
ISSN	0962-2802
卷号	28 期号:9 页码:2697-2709
摘要	Random effects two-part models have been applied to longitudinal studies for zero-inflated (or semi-continuous) data, characterized by a large portion of zero values and continuous non-zero (positive) values. Examples include monthly medical costs, daily alcohol drinks, relative abundance of microbiome, etc. With the advance of information technology for data collection and storage, the number of variables available to researchers can be rather large in such studies. To avoid curse of dimensionality and facilitate decision making, it is critically important to select covariates that are truly related to the outcome. However, owing to its intricate nature, there is not yet a satisfactory variable selection method available for such sophisticated models. In this paper, we seek a feasible way of conducting variable selection for random effects two-part models on the basis of the recently proposed "minimum information criterion" (MIC) method. We demonstrate that the MIC formulation leads to a reasonable formulation of sparse estimation, which can be conveniently solved with SAS Proc NLMIXED. The performance of our approach is evaluated through simulation, and an application to a longitudinal alcohol dependence study is provided.
关键词	High dimensional mixed effects pharmacogenetics precision medicine tuning parameter variable selection
DOI	10.1177/0962280218784712
语种	英语
资助项目	AHRQ[R01 HS 020263] ; National Natural Science Foundation of China[11771431] ; National Natural Science Foundation of China[11690015] ; Key Laboratory of RCSDS, CAS[2008DP173182]
WOS研究方向	Health Care Sciences & Services ; Mathematical & Computational Biology ; Medical Informatics ; Mathematics
WOS类目	Health Care Sciences & Services ; Mathematical & Computational Biology ; Medical Informatics ; Statistics & Probability
WOS记录号	WOS:000484532300010
出版者	SAGE PUBLICATIONS LTD
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/35523
专题	应用数学研究所
通讯作者	Liu, Lei
作者单位	1.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China 2.Washington Univ, Div Biostat, St Louis, MO 63110 USA 3.Univ Texas El Paso, Dept Math Sci, El Paso, TX 79968 USA 4.Univ Maryland, Dept Psychiat, Baltimore, MD 21201 USA
推荐引用方式 GB/T 7714	Han, Dongxiao,Liu, Lei,Su, Xiaogang,et al. Variable selection for random effects two-part models[J]. STATISTICAL METHODS IN MEDICAL RESEARCH,2019,28(9):2697-2709.
APA	Han, Dongxiao,Liu, Lei,Su, Xiaogang,Johnson, Bankole,&Sun, Liuquan.(2019).Variable selection for random effects two-part models.STATISTICAL METHODS IN MEDICAL RESEARCH,28(9),2697-2709.
MLA	Han, Dongxiao,et al."Variable selection for random effects two-part models".STATISTICAL METHODS IN MEDICAL RESEARCH 28.9(2019):2697-2709.