Metafor - rma.mv function - variance components

To: wibbeltjec at hotmail.com; r-help at r-project.org
Subject: Re: [R] Metafor - rma.mv function - variance components
From: Lists at dewey.myzen.co.uk
Date: Mon, 20 Apr 2015 20:24:48 +0000

Carlijn Wibbelink <wibbeltjec at 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!
 		 	   		  
	[[alternative HTML version deleted]]

-----Original Message-----
From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Carlijn
Wibbelink
Sent: Tuesday, April 21, 2015 10:43
To: Lists at dewey.myzen.co.uk; r-help at r-project.org
Subject: Re: [R] Metafor - rma.mv function - variance components

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)
anova(model2,model3)
anova(model2,model4)

Is it possible to receive the standard errors of the variances in metafor
(and do a Z-test)?

To: wibbeltjec at hotmail.com; r-help at r-project.org
Subject: Re: [R] Metafor - rma.mv function - variance components
From: Lists at dewey.myzen.co.uk
Date: Mon, 20 Apr 2015 20:24:48 +0000

Carlijn Wibbelink <wibbeltjec at 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!

	[[alternative HTML version deleted]]

guide.html

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)
anova(model2,model3)
anova(model2,model4)

Is it possible to receive the standard errors of the variances in
metafor (and do a Z-test)?

 > To: wibbeltjec at hotmail.com; r-help at r-project.org
 > Subject: Re: [R] Metafor - rma.mv function - variance components
 > From: Lists at dewey.myzen.co.uk
 > Date: Mon, 20 Apr 2015 20:24:48 +0000
 >
 > Carlijn Wibbelink <wibbeltjec at 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!
 > >
 > > [[alternative HTML version deleted]]
 > >
 > > ______________________________________________
 > > R-help at r-project.org