Power and sample size for multivariate logistic modeling of unmatched case-control studies

被引：9

作者：

Gail, Mitchell H. ^{[1
]}

Haneuse, Sebastien ^{[2
]}

机构：

[1] NCI, Div Canc Epidemiol & Genet, 9609 Med Ctr Dr,Room 7E138, Rockville, MD 20850 USA

[2] Harvard TH Chan Sch Publ Hlth, Boston, MA USA

来源：

STATISTICAL METHODS IN MEDICAL RESEARCH | 2019年 / 28卷 / 03期

基金：

美国国家卫生研究院;

关键词：

Unmatched case-control; logistic regression; power; sample size; retrospective information; REGRESSION; DESIGN; 2-PHASE;

D O I：

10.1177/0962280217737157

中图分类号：

R19 [保健组织与事业（卫生事业管理）];

学科分类号：

摘要：

Sample size calculations are needed to design and assess the feasibility of case-control studies. Although such calculations are readily available for simple case-control designs and univariate analyses, there is limited theory and software for multivariate unconditional logistic analysis of case-control data. Here we outline the theory needed to detect scalar exposure effects or scalar interactions while controlling for other covariates in logistic regression. Both analytical and simulation methods are presented, together with links to the corresponding software.

引用

页码：822 / 834

页数：13

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