I am conducting a meta-analysis on the effect of concientiousness on scholastic achievement in high-school students. Currently, I am struggling to find the right statistical analysis for my data structure. Several studies are reporting multiple (dependent) effect sizes. When there are multiple effect sizes that are based on the same sample, these effect sizes are dependent. One way to account for this dependency are three-level meta-analysis. The hierarchical data structre would be as follows:

  • L-1: study participants (are nested within effect sizes)
  • L-2: effect sizes (are nested within studies)
  • L-3: studies

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As I am quite confident in handling this kind of dependency using three-level meta-analysis, I struggling with another kind of depency in my data.

Some studies report effect sizes of multiple (independent) samples within one study. The effect sizes are now independent in the sense that they are based on different participants. However, all samples were tested by the same research team, using the same study design, and sometimes even in the same school/class (e.g. effect sizes are reported for boys and girls separately). Is it possible to account for this kind of dependency in three-level meta-analysis?

Best regards, Denise

  • $\begingroup$ It looks like you have a fourth level which introduces computational complexity but in theory should work. $\endgroup$ – mdewey Dec 7 '18 at 15:43

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