[R] Using compute.es and metafor together

Viechtbauer Wolfgang (STAT) wolfgang.viechtbauer at maastrichtuniversity.nl
Fri Oct 3 10:34:33 CEST 2014


Yes, that should be fine.

By the way, you do not have to name the variables 'yi' and 'vi' (if this is what you meant by 'coding these as yi and vi respectively'). Indeed, the *argument names* for supplying pre-calculated effect sizes estimates and corresponding sampling variances are 'yi' and 'vi' in various functions in the metafor package, but the *variables names* can be different. For example:

rma(yi=d, vi=var.d, data=dat)

(assuming 'd' and 'var.d' are in data frame 'dat') would be perfectly fine. And since 'yi' and 'vi' are the first two arguments of the rma() function, that can be shortened to:

rma(d, var.d, data=dat)

I tend to use 'yi' and 'vi' also as the variable names in datasets and various examples (and the escalc() function in metafor also names the estimates and corresponding variances in that way), so that leads to rma(yi, vi, data=dat), which is just shorthand for rma(yi=yi, vi=vi, data=dat), so this may be a source of potential confusion. Just wanted to clarify that you do not have to name your variables that way.

Best,
Wolfgang

--   
Wolfgang Viechtbauer, Ph.D., Statistician   
Department of Psychiatry and Psychology   
School for Mental Health and Neuroscience   
Faculty of Health, Medicine, and Life Sciences   
Maastricht University, P.O. Box 616 (VIJV1)   
6200 MD Maastricht, The Netherlands   
+31 (43) 388-4170 | http://www.wvbauer.com   

> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
> On Behalf Of Purssell, Ed
> Sent: Friday, October 03, 2014 09:39
> To: r-help at r-project.org
> Subject: [R] Using compute.es and metafor together
> 
> Dear All
> 
> For mathematically challenged people such as myself; is it ok to use the
> compute.es package to calculate effect sizes and then import the effect
> sizes d and variances of d into metafor, coding these as yi and vi
> respectively and then running the meta-analysis?  This seems easier
> because compute.es offers a lot of ways of calculating d and its variance
> using similar codes.
> 
> Thanks
> Edward
> 
> ----------------------------
> Edward Purssell PhD
> Senior Lecturer
> 
> Florence Nightingale Faculty of Nursing and Midwifery
> King's College London
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