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A Meta-Analysis Package for R

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tips:weights_in_rma.mv_models

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tips:weights_in_rma.mv_models [2021/11/08 15:17]
Wolfgang Viechtbauer
tips:weights_in_rma.mv_models [2021/11/08 15:56] (current)
Wolfgang Viechtbauer
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 ===== Weights in Models Fitted with the rma.mv() Function ===== ===== Weights in Models Fitted with the rma.mv() Function =====
  
-One of the fundamental concepts underlying a meta-analysis is the idea of weighting: More precise estimates are given more weight in the analysis then less precise estimates. In 'standard' fixed- and random-effects models (such as those that can be fitted with the ''rma()'' function), the weighting scheme is quite simple and covered in standard textbooks on meta-analysis. However, in more complex models (such as those that can be fitted with the ''rma.mv()'' function), the way estimates are weighted is more complex. Here, I will discuss some of those intricacies.+One of the fundamental concepts underlying a meta-analysis is the idea of weighting: More precise estimates are given more weight in the analysis then less precise estimates. In 'standard' equal- and random-effects models (such as those that can be fitted with the ''rma()'' function), the weighting scheme is quite simple and covered in standard textbooks on meta-analysis. However, in more complex models (such as those that can be fitted with the ''rma.mv()'' function), the way estimates are weighted is more complex. Here, I will discuss some of those intricacies.
  
 ==== Models Fitted with the rma() Function ==== ==== Models Fitted with the rma() Function ====
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 Variable ''yi'' contains the log risk ratios and variable ''vi'' the corresponding sampling variances. Variable ''yi'' contains the log risk ratios and variable ''vi'' the corresponding sampling variances.
  
-We now fit fixed- and random-effects models to these estimates.+We now fit equal- and random-effects models to these estimates.
  
 <code rsplus> <code rsplus>
tips/weights_in_rma.mv_models.txt ยท Last modified: 2021/11/08 15:56 by Wolfgang Viechtbauer