统计meta分析中的数据、比率、比率差异和比率比率:教程

Christopher James Rose, Milena Geist, Matteo Bruschettini
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引用次数: 0

摘要

本教程的重点是通过计算每个参与者可能发生零次、一次或多次的事件来评估结果的试验。试验和荟萃分析可以使用比率差异或比率比来估计计数结果的治疗效果。我们解释了为什么用荟萃分析计数数据来估计发病率比而不是比值比、风险比或风险差异更合适。我们解释计数数据是什么,试验如何估计治疗效果,如何解释这些估计,以及如何从使用计数结果进行荟萃分析的试验中提取数据。最后,我们讨论一些常见的误解和微妙之处。补充材料包括用于执行计算的Excel文件、数学背景和其他建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Count data, rates, rate differences, and rate ratios in meta-analysis: A tutorial

Count data, rates, rate differences, and rate ratios in meta-analysis: A tutorial

This tutorial focuses on trials that assess outcomes by counting events that can occur zero, one, or more than one time in each participant. Trials and meta-analyses can estimate treatment effects for count outcomes using rate differences or rate ratios. We explain why it may be appropriate to meta-analyze count data to estimate rate ratios rather than odds ratios, risk ratios, or risk differences. We explain what count data are, how trials may estimate treatment effects, how to interpret such estimates, and how to extract data from trials that use count outcomes for meta-analysis. Finally, we discuss some common misunderstandings and subtleties. Supplementary materials include an Excel file for performing calculations, mathematical background, and additional advice.

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