Difference-based meta-analytic procedures for between-participant and/or within-participant designs: A tutorial review for sports and exercise scientists
Difference-based meta-analytic procedures for between-participant and/or within-participant designs: A tutorial review for sports and exercise scientists
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DOI：
10.1080/02640410802482409
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发表时间：
2009-01-01
影响因子：
3.4
通讯作者：
Bennett, Simon J.
中科院分区：
文献类型：
--
作者：
Ashford, Derek;Davids, Keith;Bennett, Simon J.
本文的目的是提供一个当代的统计和非统计荟萃分析程序的总结，具有相关的体育科学家经常使用的实验设计类型时，检查差异/变化的依赖措施（S）作为一个或多个独立的操作（S）的结果。使用工作的例子，从观察学习的研究中的运动行为文献，我们采用随机效应模型，并给出了详细的解释的统计程序的三种类型的原始分数差异为基础的分析适用于参与者之间，参与者内，和混合参与者的设计。确定了与这些定量程序相关的主要优点和问题，并报告了用于最大限度地减少偏倚结果的商定方法，例如用于处理来自单个研究的多个依赖性措施、跨研究的设计变化、不同的度量（即原始分数和差异分数）以及样本量变化的方法。为了补充工作的例子，我们总结了进行和报告荟萃分析时需要考虑的一般因素，包括如何处理发表偏倚，关于主要研究的信息，以及处理离群值的方法。通过将这些统计和非统计元分析程序结合在一起，我们提供了澄清关键概念和原则的理解所需的工具。
The aim of this paper is to provide a contemporary summary of statistical and non-statistical meta-analytic procedures that have relevance to the type of experimental designs often used by sport scientists when examining differences/change in dependent measure(s) as a result of one or more independent manipulation(s). Using worked examples from studies on observational learning in the motor behaviour literature, we adopt a random effects model and give a detailed explanation of the statistical procedures for the three types of raw score difference-based analyses applicable to between-participant, within-participant, and mixed-participant designs. Major merits and concerns associated with these quantitative procedures are identified and agreed methods are reported for minimizing biased outcomes, such as those for dealing with multiple dependent measures from single studies, design variation across studies, different metrics (i.e. raw scores and difference scores), and variations in sample size. To complement the worked examples, we summarize the general considerations required when conducting and reporting a meta-analysis, including how to deal with publication bias, what information to present regarding the primary studies, and approaches for dealing with outliers. By bringing together these statistical and non-statistical meta-analytic procedures, we provide the tools required to clarify understanding of key concepts and principles.