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Comprehensive meta analysis outliers
Comprehensive meta analysis outliers







Then, we create a new filter variable outlier, with the value TRUE if the CI of the effect size is outside of the CI of the pooled effect. We first calculate the 95% CI for each study effect size, using the standard error of the effect size ( sqrt(vi)). To filter out outliers, we will use a boolean (TRUE/FALSE) filter variable. We can use these values to filter out outliers now. The pooled effect confidence interval stretches from \(g = 0.16\) to \(g = 0.32\). Let’s see what the upper and lower bound of the pooled effect confidence interval are: m_re $ci.lb # 0.1581353 m_re $ci.ub # 0.3203839 Here, i’ll use my m_re meta-analysis output from Chapter 5.2.2 again.

  • for which the lower bound of the 95% confidence interval of the study is higher than the higher bound of the pooled effect confidence interval (i.e., extremely large effects).
  • for which the upper bound of the 95% confidence interval of the study is lower than the lower bound of the pooled effect confidence interval (i.e., extremely small effects).
  • Using this function, we can search for all studies: To detect such outliers in our dataset, the filter function in the dplyr package we introduced in Chapter 3.3.3 comes in handy again.
  • 11.1.1 Three-level meta-analytic modelsħ.3.1 Searching for extreme effect sizes (outliers)Ī common method to detect outliers directly is to define a study as an outlier if the study’s confidence interval does not overlap with the confidence interval of the pooled effect.
  • 11.1 Meta-Analysis is multi-level (optional).
  • 10.1.5 Duval & Tweedie’s trim-and-fill procedure.
  • 10.1.4 Testing for funnel plot asymmetry using Egger’s test.
  • 7.3.1 Searching for extreme effect sizes (outliers).
  • 7.3 Detecting outliers & influential cases.
  • 7.2 Assessing the heterogeneity of your pooled effect size.
  • 5.2.1 Estimators for tau 2 in the random-effects-model.
  • 4.1 Calculating standardized mean differences.
  • 2.1 Getting RStudio to run on your computer.








  • Comprehensive meta analysis outliers