[R] Metafor - rma.mv function - variance components
wibbeltjec at hotmail.com
Tue Apr 21 10:42:53 CEST 2015
Thank you for your reaction, it worked.
However, I'm wondering if this is the right way to test whether there is significant variation on one of the two levels. The results of the anova tests do not correspond to the results of the Z-test in metaSEM. (In metaSEM only one of the variances is significant, but when I use the anova test in metafor, both variances are significant). But maybe I made a mistake. This is my syntax:
model2 <- rma.mv(y, v, random = list(~ 1 | y, ~ 1 | ID), data=dat)
model3 <- rma.mv(y, v, random = list(~ 1 | y, ~ 1 | ID), sigma2=c(NA,0), data=dat)
model4 <- rma.mv(y, v, random = list(~ 1 | y, ~ 1 | ID), sigma2=c(0,NA), data=dat)
Is it possible to receive the standard errors of the variances in metafor (and do a Z-test)?
> To: wibbeltjec op hotmail.com; r-help op r-project.org
> Subject: Re: [R] Metafor - rma.mv function - variance components
> From: Lists op dewey.myzen.co.uk
> Date: Mon, 20 Apr 2015 20:24:48 +0000
> Carlijn Wibbelink <wibbeltjec op hotmail.com> wrote :
> Dear Carlijn
> I think that if you set sigma2 to a vector of length 2 it will be possible.
> > Hi all,
> > I have a question about metafor and the rma.mv function. I have fitted a
> > multivariate model (effect sizes are nested within studies) and I've found two
> > variances:
> > Variance Components:
> > estim sqrt nlvls fixed factor
> > sigma^2.1 0.0257 0.1602 72 no y
> > sigma^2.2 0.0694 0.2635 10 no ID
> > I want to test whether there is significant variantion between the effect sizes
> > within studies (sigma^2.1: 0.0257) and/or between studies (sigma^2.2: 0.0694).
> > In metaSEM you can fix for example the variance within studies (sigma^2.1) to
> > zero to test whether there is a significant difference in fit between the models
> > (and if so, then there is significant heterogeneity between the effect sizes
> > within studies). I was wondering if this is also possible in metafor. If I fix
> > sigma2 to zero, then both variances are fixed to zero. However, I want to fix
> > only one variance to zero.
> > I hope that someone can help me. Thank you in advance!
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