[R-meta] Subgroup analysis with RVE
Hi Thank you, sorry I did not explain clearly. I estimated effects within subgroups with RVE (intercept only model in each), but I did not do a between-groups test of significance. I did fit a model with a between groups covariate (subgroups coded dichotomously: high/low), which I took to be the equivalent of a meta-regression with a dichotomous predictor. Best Ioana On Thu, Dec 3, 2020 at 9:20 AM Viechtbauer, Wolfgang (SP) <
wolfgang.viechtbauer at maastrichtuniversity.nl> wrote:
Dear Ioana,
I am not sure why you think that a test of that moderators is not useful
when the number of effect sizes is so different between the two groups. All
else equal, power will indeed be lower as opposed to the case where k is
similar for the two groups, but that will be the case no matter how you
analyze the data (via meta-regression or subgrouping).
This aside, I am a bit confused by your question. A subgroup analysis is
just that: Fitting a particular model in a subgroup of the studies. That
can be done with or without RVE. You seem to have done this already ("I
estimated effects in the high and low subgroup separately").
Best,
Wolfgang
-----Original Message----- From: R-sig-meta-analysis [mailto:
r-sig-meta-analysis-bounces at r-project.org]
On Behalf Of Ioana Cristea Sent: Wednesday, 25 November, 2020 15:43 To: r-sig-meta-analysis at r-project.org Subject: [R-meta] Subgroup analysis with RVE Dear all I am running a meta-analysis with robust variance estimation (RVE) and my focus is on a categorical variable (a risk of bias domain variable, coded dichotomously, high vs low, in the database "0" for low risk and "1" for high risk). I estimated effects in the high and low subgroup separately, each in an intercept only model. I also ran the RVE model estimating the between-study effect of covariates, including my predictor (which is a between study variable) as a covariate (it was not significant). I think a big problem is that the two subgroups delineated by the categorical variable are very uneven in terms of the information contained (one has 45 effect sizes, one 13) and in my view a test of significance for
differences
between them is not useful. One of my co-authors would also like us to run a subgroup analysis. I am not sure how to do that, if it is possible with RVE and if it adds
anything
to the model estimating between-study covariates, which I already ran. Thank you! Ioana -- Ioana-Alina Cristea, Ph.D. Assistant Professor Department of Brain and Behavioral Sciences University of Pavia, Piazza Botta 11, 27100 Pavia, Italy Research affiliate METRICS (Meta-research Innovation Center at Stanford) Stanford University, California, USA Editorial Advisory Board Lancet Psychiatry <https://www.thelancet.com/journals/lanpsy/home> International Editorial Board BJPsych Open <https://www.cambridge.org/core/journals/bjpsych-open> ORCid: http://orcid.org/0000-0002-9854-7076 Publons: https://publons.com/author/1196647/ioana-alina-cristea#profile Researchgate: https://www.researchgate.net/profile/Ioana_Cristea Twitter: https://twitter.com/IoanaA_Cristea
Ioana-Alina Cristea, Ph.D. Assistant Professor Department of Brain and Behavioral Sciences University of Pavia, Piazza Botta 11, 27100 Pavia, Italy Research affiliate METRICS (Meta-research Innovation Center at Stanford) Stanford University, California, USA Editorial Advisory Board Lancet Psychiatry <https://www.thelancet.com/journals/lanpsy/home> International Editorial Board BJPsych Open <https://www.cambridge.org/core/journals/bjpsych-open> ORCid: http://orcid.org/0000-0002-9854-7076 Publons: https://publons.com/author/1196647/ioana-alina-cristea#profile Researchgate: https://www.researchgate.net/profile/Ioana_Cristea Twitter: https://twitter.com/IoanaA_Cristea [[alternative HTML version deleted]]