Peters Jaime L, Mengersen Kerrie L
School of Mathematical Sciences, Queensland University of Technology, Australia.
J Eval Clin Pract. 2008 Oct;14(5):941-50. doi: 10.1111/j.1365-2753.2008.01010.x.
RATIONALE, AIMS AND OBJECTIVES: Repeated measures studies are found in many areas of research, particularly in areas of healthcare. There is currently little information available to inform the method of meta-analysis of repeated measures studies so that the structural dependence of the data is appropriately accommodated and the findings are meaningful.
Using a published meta-analysis on the impact of diet advice on weight reduction of obese or overweight individuals, we demonstrate possible approaches for repeated measures meta-analysis. These approaches differ in terms of the type of result obtained (e.g. effect at a particular time-point, trend over time, change between time-points) and the data needed for the analysis (e.g. means, regression slope estimates). Some approaches involve violating assumptions of independence in the data structure and so to investigate the impact of this violation a simulation study is carried out.
The different approaches described for the meta-analyses of repeated measures studies can all provide useful effect estimates depending on the question to be addressed by the meta-analysis. However, violation of the independence assumption in some approaches can lead to biased estimates.
In practice, the methods available to carry out meta-analyses of repeated measures studies will not only depend upon the question of interest, but also on the data available from the primary studies.
原理、目的和目标：重复测量研究在许多研究领域都有发现，尤其是在医疗保健领域。目前几乎没有可用信息来指导重复测量研究的荟萃分析方法，以便适当地考虑数据的结构依赖性并使研究结果具有意义。
利用一项已发表的关于饮食建议对肥胖或超重个体体重减轻影响的荟萃分析，我们展示了重复测量荟萃分析的可能方法。这些方法在获得的结果类型（例如特定时间点的效应、随时间的趋势、时间点之间的变化）和分析所需的数据（例如均值、回归斜率估计值）方面有所不同。一些方法涉及违反数据结构中的独立性假设，因此为了研究这种违反的影响，进行了一项模拟研究。
根据荟萃分析要解决的问题，为重复测量研究的荟萃分析描述的不同方法都可以提供有用的效应估计值。然而，某些方法中违反独立性假设可能会导致估计偏差。
在实践中，进行重复测量研究荟萃分析的可用方法不仅取决于感兴趣的问题，还取决于原始研究中可用的数据。
