[R-meta] Fwd: predicted intervals in metafor
r@yn@ud@@rm@trong @ending from gm@il@com
Tue Jun 5 17:56:56 CEST 2018
I would like to know what is the default method in random effects
meta-analysis in metafor.
My effect size (cohen's d) is not normally distributed. Does that matter?
Please reply as soon as possible.
---------- Forwarded message ----------
From: Raynaud Armstrong <raynaud.armstrong using gmail.com>
Date: Sat, Dec 16, 2017 at 6:34 AM
Subject: Re: [R-meta] predicted intervals in metafor
To: "Viechtbauer Wolfgang (SP)" <wolfgang.viechtbauer@
Perfect - it worked!
On Fri, Dec 15, 2017 at 3:38 AM, Viechtbauer Wolfgang (SP) <
wolfgang.viechtbauer using maastrichtuniversity.nl> wrote:
> Dear Raynaud,
> Once you have the SMD values and corresponding sampling variances, the
> code is the same. Here is an example:
> ### load data
> dat <- get(data(dat.normand1999))
> ### calculate SMDs and corresponding sampling variances
> dat <- escalc(measure="SMD", m1i=m1i, sd1i=sd1i, n1i=n1i, m2i=m2i,
> sd2i=sd2i, n2i=n2i, data=dat)
> ### meta-analysis of SMD values using a random-effects model
> res <- rma(yi, vi, data=dat)
> ### get prediction/credibility interval
> If you have calculated the SMD values and variances yourself, you can skip
> the escalc() step and go straight to rma(). Adjust variables names as
> -----Original Message-----
> From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bo
> unces using r-project.org] On Behalf Of Raynaud Armstrong
> Sent: Friday, 15 December, 2017 1:37
> To: r-sig-meta-analysis using r-project.org
> Subject: [R-meta] predicted intervals in metafor
> Hi there,
> I would like to calculate predicted intervals in addition to my pooled
> estimate and CIs as I have plenty of between-study variation in my
> meta-analysis. I am using metafor package and my summary estimated is an
> effect size (SMD) and not odds ratios. The examples I have come across
> mainly focus on odds ratios and I wonder what to do for SMDs.
> I would appreciate if someone could suggest what function to use.
> Thank you,
[[alternative HTML version deleted]]
More information about the R-sig-meta-analysis