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首页> 外文期刊>International Journal of Environmental Research and Public Health >Computing Power and Sample Size for Informational Odds Ratio?
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Computing Power and Sample Size for Informational Odds Ratio?

机译:信息几率的计算能力和样本量?

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The informational odds ratio (IOR) measures the post-exposure odds divided by the pre-exposure odds (i.e., information gained after knowing exposure status). A desirable property of an adjusted ratio estimate is collapsibility, wherein the combined crude ratio will not change after adjusting for a variable that is not a confounder. Adjusted traditional odds ratios (TORs) are not collapsible. In contrast, Mantel-Haenszel adjusted IORs, analogous to relative risks (RRs) generally are collapsible. IORs are a useful measure of disease association in case-referent studies, especially when the disease is common in the exposed and/or unexposed groups. This paper outlines how to compute power and sample size in the simple case of unadjusted IORs.
机译:信息优势率(IOR)衡量的是曝光后优势除以曝光前优势(即知道曝光状态后获得的信息)。调整比率估计值的理想属性是可折叠性,其中在调整了不是混杂因素的变量之后,合并的原始比率将不会更改。调整后的传统优势比(TOR)不可折叠。相反,Mantel-Haenszel调整后的IOR(类似于相对风险(RR))通常是可折叠的。在病例参考研究中,IOR是衡量疾病关联性的一种有用方法,尤其是当疾病在暴露和/或未暴露人群中很常见时。本文概述了在未经调整的IOR的简单情况下如何计算功效和样本数量。

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