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对整群随机试验数据进行重新分析以探讨模型选择对优势比估计值的影响:研究方案

Re-analysis of data from cluster randomised trials to explore the impact of model choice on estimates of odds ratios: study protocol.

作者信息

Hemming Karla, Thompson Jacqueline Y, Taljaard Monica, Watson Samuel I, Kasza Jessica, Thompson Jennifer A, Kahan Brennan C, Copas Andrew J

机构信息

Institute of Applied Health Research, University of Birmingham, Birmingham, UK.

Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Canada.

出版信息

Trials. 2024 Dec 18;25(1):818. doi: 10.1186/s13063-024-08653-1.

Abstract

BACKGROUND

There are numerous approaches available to analyse data from cluster randomised trials. These include cluster-level summary methods and individual-level methods accounting for clustering, such as generalised estimating equations and generalised linear mixed models. There has been much methodological work showing that estimates of treatment effects can vary depending on the choice of approach, particularly when estimating odds ratios, essentially because the different approaches target different estimands.

METHODS

In this manuscript, we describe the protocol for a planned re-analysis of data from a large number of cluster randomised trials. Our main objective is to examine empirically whether and how odds ratios estimated using different approaches (for both primary and secondary binary outcomes) vary in cluster randomised trials. We describe the methods that will be used to identify the datasets for inclusion and how they will be analysed and reported.

DISCUSSION

There have been a number of small comparisons of empirical differences between the different approaches to analysis for CRTs. The systematic approach outlined in this protocol will allow a much deeper understanding of when there are important choices around the model approach and in which settings. This will be of importance given the heightened awareness of the importance of estimands and the specification of statistical analysis plans.

摘要

背景

有多种方法可用于分析整群随机试验的数据。这些方法包括整群水平汇总方法以及考虑聚类的个体水平方法,如广义估计方程和广义线性混合模型。有大量方法学研究表明,治疗效果的估计值可能因方法选择而异,尤其是在估计比值比时,主要原因是不同方法针对的是不同的估计量。

方法

在本手稿中,我们描述了对大量整群随机试验数据进行计划中的重新分析的方案。我们的主要目标是通过实证研究,考察在整群随机试验中,使用不同方法(针对主要和次要二元结局)估计的比值比是否以及如何不同。我们描述了用于确定纳入数据集的方法,以及将如何对其进行分析和报告。

讨论

对于整群随机试验的不同分析方法之间的实证差异,已经有一些小规模比较。本方案中概述的系统方法将使我们能更深入地理解何时围绕模型方法存在重要选择以及在哪些情况下存在这种选择。鉴于对估计量的重要性以及统计分析计划的规范的认识不断提高,这将具有重要意义。

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