[R-meta] Question about escalc, proportion ES, and nested data

[Harris, Jordan L]

Hi List Members,

I am a graduate student who is new to R and meta-analyses, and I have been running into problems getting my code sorted out.

I am conducting a meta-analysis to explore how the structure of psychopathology changes across childhood and adolescence. My effect size of interest is represented by a proportion score that is conceptualized as ratio of variance accounted for by a general factor, called "general_es" (i.e., general / general + specific). These data do not currently have a sampling variance, nor have transformed effect sizes been calculated. I have 3 levels of nested data: Level 1 = "timepoint_id", Level 2 = "sample_id", Level 1 = "study_id" which account for non-independence of data. Here, I will call my data file "dat."


  1.  How should I structure the escalc command to derive a "yi" and "V" values needed for the rma.mv analysis? Would my measure be "PLO"?

  1.  Would this structure be acceptable: rma.mv(yi, vi, random = ~ 1 | study_id/sample_id/timepoint_id, data=dat)?

Thanks,
Jordan

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