Variable selection for random effects two-part models
文献类型：期刊论文
| 作者 | Han, Dongxiao2; Liu, Lei3; Su, Xiaogang1; Johnson, Bankole4; Sun, Liuquan2
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| 刊名 | STATISTICAL METHODS IN MEDICAL RESEARCH
 |
| 出版日期 | 2019-09-01 |
| 卷号 | 28期号:9页码:2697-2709 |
| ISSN号 | 0962-2802 |
| 关键词 | High dimensional mixed effects pharmacogenetics precision medicine tuning parameter variable selection |
| DOI | 10.1177/0962280218784712 |
| 英文摘要 | 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. |
| 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 |
| 语种 | 英语 |
| 出版者 | SAGE PUBLICATIONS LTD |
| WOS记录号 | WOS:000484532300010 |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/35522]  |
| 专题 | 应用数学研究所 |
| 通讯作者 | Liu, Lei |
| 作者单位 | 1.Univ Texas El Paso, Dept Math Sci, El Paso, TX 79968 USA 2.Chinese Acad Sci, Acad Math & Syst Sci, Beijing, Peoples R China 3.Washington Univ, Div Biostat, St Louis, MO 63110 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. |
入库方式： OAI收割
来源：数学与系统科学研究院
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