tips:i2_multilevel_multivariate
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tips:i2_multilevel_multivariate [2021/01/06 10:58] – [General Equation for I^2] Wolfgang Viechtbauer | tips:i2_multilevel_multivariate [2021/01/06 11:02] – Wolfgang Viechtbauer | ||
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- | ===== I^2 for Multilevel and Multivariate Models ===== | + | ===== $\boldsymbol{I^2}$ for Multilevel and Multivariate Models ===== |
The $I^2$ statistic was introduced by Higgins and Thompson in their seminal 2002 paper and has become a rather popular statistic to report in meta-analyses, | The $I^2$ statistic was introduced by Higgins and Thompson in their seminal 2002 paper and has become a rather popular statistic to report in meta-analyses, | ||
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- | ==== General Equation for $\boldsymbol{I}^2$ ==== | + | ==== General Equation for $\boldsymbol{I^2}$ ==== |
Before we continue with more complex models, it is useful to point out a more general equation for computing $I^2,$ which also applies to models involving moderator variables (i.e., mixed-effects meta-regression models). This will also become important when dealing with models where sampling errors are no longer independent. So, let us define $$\mathbf{P} = \mathbf{W} - \mathbf{W} \mathbf{X} (\mathbf{X}' | Before we continue with more complex models, it is useful to point out a more general equation for computing $I^2,$ which also applies to models involving moderator variables (i.e., mixed-effects meta-regression models). This will also become important when dealing with models where sampling errors are no longer independent. So, let us define $$\mathbf{P} = \mathbf{W} - \mathbf{W} \mathbf{X} (\mathbf{X}' |
tips/i2_multilevel_multivariate.txt · Last modified: 2022/10/24 10:10 by Wolfgang Viechtbauer