Extreme-value sampling design is cost-beneficial only with a valid statistical approach for exposure-secondary outcome association analyses
文献类型:期刊论文
作者 | Zhang, Hang3,6; Bi, Wenjian4; Cui, Yuehua1; Chen, Honglei2; Chen, Jinbo5; Zhao, Yanlong3,6; Kang, Guolian4 |
刊名 | STATISTICAL METHODS IN MEDICAL RESEARCH
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出版日期 | 2020-02-01 |
卷号 | 29期号:2页码:466-480 |
关键词 | Secondary outcome exposure extreme-value sampling design primary outcome cost-effective |
ISSN号 | 0962-2802 |
DOI | 10.1177/0962280219839093 |
英文摘要 | In epidemiology cohort studies, exposure data are collected in sub-studies based on a primary outcome (PO) of interest, as with the extreme-value sampling design (EVSD), to investigate their correlation. Secondary outcomes (SOs) data are also readily available, enabling researchers to assess the correlations between the exposure and the SOs. However, when the EVSD is used, the data for SOs are not representative samples of a general population; thus, many commonly used statistical methods, such as the generalized linear model (GLM), are not valid. A prospective likelihood method has been developed to associate SOs with single-nucleotide polymorphisms under an extreme phenotype sequencing design. In this paper, we describe the application of the prospective likelihood method (STEVSD) to exposure-SO association analysis under an EVSD. We undertook extensive simulations to assess the performance of the STEVSD method in associating binary and continuous exposures with SOs, comparing it to the simple GLM method that ignores the EVSD. To demonstrate the cost-benefit of the STEVSD method, we also mimicked the design of two new retrospective studies, as would be done in actual practice, based on the PO of interest, which was the same as the SO in the EVSD study. We then analyzed these data by using the GLM method and compared its power to that of the STEVSD method. We demonstrated the usefulness of the STEVSD method by applying it to a benign ethnic neutropenia dataset. Our results indicate that the STEVSD method can control type I error well, whereas the GLM method cannot do so owing to its ignorance of EVSD, and that the STEVSD method is cost-effective because it has statistical power similar to that of two new retrospective studies that require collecting new exposure data for selected individuals. |
资助项目 | American Lebanese Syrian Associated Charities (ALSAC) ; NHLBI at the NIH ; NIDDK at the NIH ; National Institutes of Health[HHSN268200782096C] ; National Institutes of Health[HHSN268201100011I] ; National Key Research and Development Program of China[2016YFB0901902] ; National Natural Science Foundation of China[61622309] |
WOS研究方向 | Health Care Sciences & Services ; Mathematical & Computational Biology ; Medical Informatics ; Mathematics |
语种 | 英语 |
WOS记录号 | WOS:000513264200010 |
出版者 | SAGE PUBLICATIONS LTD |
源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/50747] ![]() |
专题 | 中国科学院数学与系统科学研究院 |
通讯作者 | Zhao, Yanlong; Kang, Guolian |
作者单位 | 1.Michigan State Univ, Dept Stat & Probabil, E Lansing, MI 48824 USA 2.Michigan State Univ, Dept Epidemiol & Biostat, E Lansing, MI 48824 USA 3.Univ Chinese Acad Sci, Sch Math Sci, Beijing, Peoples R China 4.St Jude Childrens Res Hosp, Dept Biostat, 332 N Lauderdale St, Memphis, TN 38105 USA 5.Univ Penn, Dept Biostat Epidemiol & Informat, Philadelphia, PA 19104 USA 6.Chinese Acad Sci, Key Lab Syst & Control, Acad Math & Syst Sci, Beijing, Peoples R China |
推荐引用方式 GB/T 7714 | Zhang, Hang,Bi, Wenjian,Cui, Yuehua,et al. Extreme-value sampling design is cost-beneficial only with a valid statistical approach for exposure-secondary outcome association analyses[J]. STATISTICAL METHODS IN MEDICAL RESEARCH,2020,29(2):466-480. |
APA | Zhang, Hang.,Bi, Wenjian.,Cui, Yuehua.,Chen, Honglei.,Chen, Jinbo.,...&Kang, Guolian.(2020).Extreme-value sampling design is cost-beneficial only with a valid statistical approach for exposure-secondary outcome association analyses.STATISTICAL METHODS IN MEDICAL RESEARCH,29(2),466-480. |
MLA | Zhang, Hang,et al."Extreme-value sampling design is cost-beneficial only with a valid statistical approach for exposure-secondary outcome association analyses".STATISTICAL METHODS IN MEDICAL RESEARCH 29.2(2020):466-480. |
入库方式: OAI收割
来源:数学与系统科学研究院
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