Preparing for a meta-analysis of rates: extracting effect sizes and standard errors from studies of count outcomes with person-time denominators.

IF 2.5 3区 医学 Q2 PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH
Matthew Spittal
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引用次数: 0

Abstract

Background: Formulas for the extraction of continuous and binary effect sizes that are entered into a meta-analysis are readily available. Only some formulas for the extraction of count outcomes have been presented previously. The purpose of this methodological article is to present formulas for extracting effect sizes and their standard errors for studies of count outcomes with person-time denominators.

Methods: Formulas for the calculation of the number of events in a study and the corresponding person time in which these events occurred are presented. These formulas are then used to estimate the relevant effect sizes and standard errors of interest. These effect sizes are rates, rate ratios and rate differences for a two-group comparison and rate ratios and rate differences for a difference-in-difference design.

Results: Two studies from the field of suicide prevention are used to demonstrate the extraction of the information required to estimate effect sizes and standard errors. In the first example, the rate ratio for a two-group comparison was 0.957 (standard error of the log rate ratio, 0.035), and the rate difference was -0.56 per 100,000 person years (standard error 0.44). In the second example, the rate ratio for a difference-in-difference analysis was 0.975 (standard error of the log rate ratio 0.036) and the rate difference was -0.30 per 100,000 person years (standard error 0.42).

Conclusions: The application of these formulas enables the calculation of effect sizes that may not have been presented in the original study. This reduces the need to exclude otherwise eligible studies from a meta-analysis, potentially reducing one source of bias.

为比率的荟萃分析做准备:从具有人时间分母的计数结果的研究中提取效应大小和标准误差。
背景:在荟萃分析中提取连续效应和二元效应的公式是很容易获得的。以前只提出了一些提取计数结果的公式。这篇方法学文章的目的是提出提取效应量及其标准误差的公式,用于研究带有个人时间分母的计数结果。方法:给出了一项研究中事件数的计算公式以及这些事件发生的相应时间。然后使用这些公式来估计相关的效应大小和感兴趣的标准误差。这些效应量是两组比较的比率、比率比和比率差异,以及差中差设计的比率比和比率差异。结果:来自自杀预防领域的两项研究被用来证明提取所需的信息来估计效应大小和标准误差。在第一个示例中,两组比较的比率比率为0.957(对数比率的标准误差为0.035),比率差异为-0.56 / 100,000人年(标准误差为0.44)。在第二个示例中,差中差分析的比率为0.975(对数比率的标准误差为0.036),比率差为每100,000人年-0.30(标准误差为0.42)。结论:这些公式的应用可以计算原研究中可能没有提出的效应量。这减少了从荟萃分析中排除其他合格研究的需要,潜在地减少了一个偏倚来源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Injury Prevention
Injury Prevention 医学-公共卫生、环境卫生与职业卫生
CiteScore
5.30
自引率
2.70%
发文量
68
审稿时长
6-12 weeks
期刊介绍: Since its inception in 1995, Injury Prevention has been the pre-eminent repository of original research and compelling commentary relevant to this increasingly important field. An international peer reviewed journal, it offers the best in science, policy, and public health practice to reduce the burden of injury in all age groups around the world. The journal publishes original research, opinion, debate and special features on the prevention of unintentional, occupational and intentional (violence-related) injuries. Injury Prevention is online only.
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