Res Synth Methods - A basic introduction to fixed-effect and random-effects models for meta-analysis.

Tópicos

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Resumo

There are two popular statistical models for meta-analysis, the fixed-effect model and the random-effects model. The fact that these two models employ similar sets of formulas to compute statistics, and sometimes yield similar estimates for the various parameters, may lead people to believe that the models are interchangeable. In fact, though, the models represent fundamentally different assumptions about the data. The selection of the appropriate model is important to ensure that the various statistics are estimated correctly. Additionally, and more fundamentally, the model serves to place the analysis in context. It provides a framework for the goals of the analysis as well as for the interpretation of the statistics. In this paper we explain the key assumptions of each model, and then outline the differences between the models. We conclude with a discussion of factors to consider when choosing between the two models. Copyright ? 2010 John Wiley & Sons, Ltd.

Resumo Limpo

two popular statist model metaanalysi fixedeffect model randomeffect model fact two model employ similar set formula comput statist sometim yield similar estim various paramet may lead peopl believ model interchang fact though model repres fundament differ assumpt data select appropri model import ensur various statist estim correct addit fundament model serv place analysi context provid framework goal analysi well interpret statist paper explain key assumpt model outlin differ model conclud discuss factor consid choos two model copyright john wiley son ltd

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