[R-meta] Weight argument in rma.uni models

Wed, Oct 2, 2019 6:29 AM

rma.uni() has a 'weighted' argument (which is TRUE by default):

https://wviechtb.github.io/metafor/reference/rma.uni.html

Best,
Wolfgang

-----Original Message-----
From: Tina Dudenh?ffer [mailto:tina.dudenhoeffer at gmail.com] 
Sent: Wednesday, 02 October, 2019 15:00
To: Viechtbauer, Wolfgang (SP)
Cc: r-sig-meta-analysis at r-project.org
Subject: Re: [R-meta] Weight argument in rma.uni models

Dear Wolfgang,

thanks for your quick response.  I, indeed, mean rma.mv()! 

Considering the default is the inverse variance weight, would you suggest I stick to my res5 version?

I saw somewhere else the argument ?weighted=TRUE? added - but when looking the documentation, I don?t see it. I suppose it?s not necessary or at least not in my case?

Thank you so much!

Tina

On Oct 2, 2019, at 2:49 PM, Viechtbauer, Wolfgang (SP) <wolfgang.viechtbauer at maastrichtuniversity.nl> wrote:

Dear Tina,

I assume you mean the rma.mv() function, not rma.uni().

If you don't specify W, then weights are applied automatically. See:

https://wviechtb.github.io/metafor/reference/rma.mv.html

and search for "Together with the variance-covariance matrix of the sampling errors". However, for the model you show, the model implied marginal variance-covariance matrix of the observed outcomes (M) is not diagonal, but also has off-diagonal elements. So, there is actually an entire weight matrix.

Also, in 'res5', M (and hence the weight matrix W = M^(-1)) will incorporate the estimates of the two variance components (for EffectSize_ID_NEW and Study), while 'res6' only uses 1/Variance_New as the weights and doesn't consider the two variance components.

Best,
Wolfgang

-----Original Message-----
From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces at r-project.org] On Behalf Of Tina Dudenh?ffer
Sent: Wednesday, 02 October, 2019 13:48
To: r-sig-meta-analysis at r-project.org
Subject: [R-meta] Weight argument in rma.uni models

Dear all,

I am working with the rma.uni function to fit a multivariate random effects model.

I see that the W argument is an optional argument to specify a user-defined weight matrix. I was curious if any weight is applied if I don?t specify this argument. 
Specifically, I am wondering if the inverse variance weight is applied ?automatically?, considering I am specifying the V argument in the model itself.

In terms of my model, I am wondering about the difference between these:

res5 <- rma.mv(EffectSize_NEW, Variance_New, method="REML",random = list(~ 1 | EffectSize_ID_NEW, ~ 1 | Study), data=Data)
res5

res6 <- rma.mv(EffectSize_NEW, Variance_New, W=weight, method="REML",random = list(~ 1 | EffectSize_ID_NEW, ~ 1 | Study), data=Data)
res6

Note: the argument weight in my dataset is simply: 1/Variance_New

Hope this is all clear.

Many thanks and kind regards,
Tina

[R-meta] Weight argument in rma.uni models

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