[R-meta] Quick question about the metafor package: log-odds with rma()
jepusto at gmail.com
Sun Sep 17 17:58:57 CEST 2017
(Recognizing that your question was addressed to Wolfgang, I will offer a response anyways.)
I think it is hard to judge whether the analysis you propose is appropriate or not, without having more information about the variables involved and whether they are measured in consistent fashion across the 4 studies in your analysis.
The analysis you describe is not inappropriate--and indeed it is probably a good thing to run as a first step. However, if the four studies are indeed close replications, you might want to consider pooling the raw data from across the four studies and analyzing the combined data as you would a block-randomized trial. I think this would likely provide more accurate estimates and more powerful tests of the focal effects, although again it is hard to say for certain without knowing more details.
Sent from my iPhone
> On Sep 17, 2017, at 9:26 AM, Flávio Azevedo <falafla at gmail.com> wrote:
> Dear Dr. Wolfgang Viechtbauer,
> I am a Ph.D. candidate at Cologne University and I am conducting a
> mini-meta analysis (within paper effects) of log-odds ensuing from 4
> studies of a given DV on a set of continuous and categorical covariates.
> All models are equal across the 4 studies.
> Given this, in R, I am using the metafor function rma(yi, vi, ...) where
> yi=estimates of log-odds, and vi=standard errors ensuing from the glm
> models, using the Hartung-Knapp correction. And I would like to know if
> using log-odds as effect size estimates is appropriate.
> My question stems from the simplicity of this approach, which in statistics
> is almost never the case. Thank you very much for your time and work on
> All the best,
> \Flavio Azevedo
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