[R-meta] Freeman-Tukey double arcsine transformation and harmonic mean

Naike Wang wangnaike1989 at gmail.com
Fri Jul 7 15:25:25 CEST 2017


Hi all,
I have two questions.
1) In this article
<https://mail.jjay.cuny.edu/owa/redir.aspx?C=jnnID1xyBS33HM9BECtjC_Z23ilF54mDEf0zdCS88qMPhZkvMsXUCA..&URL=http%3a%2f%2fwww.metafor-project.org%2fdoku.php%2fanalyses%3amiller1978>,
Dr. Wolfgang Viechtbauer used the harmonic mean of the sample sizes to
back-transform the estimated average transformed proportion (the pooled
proportion). If I don't want to use the harmonic mean,  is it possible to
use the *transf.ipft*, instead of the *transf**=**transf.ipft.hm
<http://transf.ipft.hm>*, to get the pooled proportion? If so, how do I do
that?

2) One of the reasons I asked the question is due to this article:
Meta-analysis
of prevalence
<https://drive.google.com/open?id=0B41wTxciaMqtNXVSNEFGazdPWFU>. The
authors of this article developed an Exel-based meta-analysis add-in
(MetaXL). MetaXL uses a different method to perform the double arcsine
transformation. The differences are two-fold.
First, MetaXL uses a different definition of  the Freeman-Tukey
transformation. The PFT values (yi) are twice as large as the values
computed by metafor and the variances (vi) are four times as large. The
different definitions are also explained here
<http://www.metafor-project.org/doku.php/faq#how_is_the_freeman-tukey_trans>
.
Second, it does not use the harmonic mean to perform the
back-transformation. According to the authors, it is better not to use the
harmonic mean because their simulation studies suggest that the harmonic
mean is not stable.
Basically, I'm asking how to get metafor to get the same results as
obtained in MetaXL? Do you agree with the MetaXL authors that it is better
not to use the harmonic mean?

I hope my questions make sense. Feel free to ask me anything if you don't
understand.

P.S. Dowload MetaXL here: http://www.epigear.com/index_files/metaxl.html
P.S.S. After you install MetaXL, open example "SchizophreniaPrev" to get a
sense of how it performs meta-analysis of proportions.

Cheers,
Naike

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