[R-meta] Quick question about the metafor package: log-odds with rma()
falafla at gmail.com
Sun Sep 17 19:18:01 CEST 2017
(and James and Wolfang)
Thank you for your kind and explanatory answer James. And apologies for
addressing it to Wolfgang, I now understand how this works.
I will proceed with your suggestions and also estimate the log-odds we are
interested based on the pooled data.
Lastly, I leave the below information in case it changes your prior
suggestion. The data ensue from 4 surveys/studies in Social Sciences,
mostly political variables. Three samples used large convenience samples,
and 1 is representative w.r.t. the target population via a professional
survey company. All estimates ensue from Logistic regressions with the
form: glm(DV ~ IV + same.controls, family = binomial(link='logit').
All the best,
On 17 September 2017 at 17:58, James Pustejovsky <jepusto at gmail.com> wrote:
> (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
> > is almost never the case. Thank you very much for your time and work on
> > this,
> > All the best,
> > \Flavio Azevedo
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