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Multilevel Multivariate Meta-analysis with Application to Choice Overload

机译:多级多变量Meta分析,应用于选择过载

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摘要

We introduce multilevel multivariate meta-analysis methodology designed to account for the complexity of contemporary psychological research data. Our methodology directly models the observations from a set of studies in a manner that accounts for the variation and covariation induced by the facts that observations differ in their dependent measures and moderators and are nested within, for example, papers, studies, groups of subjects, and study conditions. Our methodology is motivated by data from papers and studies of the choice overload hypothesis. It more fully accounts for the complexity of choice overload data relative to two prior meta-analyses and thus provides richer insight. In particular, it shows that choice overload varies substantially as a function of the six dependent measures and four moderators examined in the domain and that there are potentially interesting and theoretically important interactions among them. It also shows that the various dependent measures have differing levels of variation and that levels up to and including the highest (i.e., the fifth, or paper, level) are necessary to capture the variation and covariation induced by the nesting structure. Our results have substantial implications for future studies of choice overload.
机译:我们介绍多级多变量Meta分析方法,旨在考虑当代心理研究数据的复杂性。我们的方法直接模拟了一系列研究的观察,这些研究的方式考虑了观察结果在其依赖措施和主持人中不同的事实诱导的,并且嵌套在例如论文,研究,受试者组中,和学习条件。我们的方法是由论文的数据和选择重载假设的研究。它更完全占选择相对于两个先前的Meta-Analys的复杂性的复杂性,从而提供更丰富的洞察力。特别地,它表明选择过载基本上随着六个依赖性措施的函数和域中检测的四个主持人而且,它们之间存在潜在的有趣和理论上重要的相互作用。它还表明,各种依赖性措施具有不同的变化水平,并且该水平达到和包括最高(即第五或纸张,水平),以捕获嵌套结构引起的变化和共变量。我们的结果对未来的选择过载研究具有很大的影响。

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