Message-ID: <cafc07752849492b99ecf9a289a466c0@UM-MAIL3214.unimaas.nl>
Date: 2018-09-25T15:32:01Z
From: Wolfgang Viechtbauer
Subject: [R-meta] Significance of the individual effects
In-Reply-To: <EC45C6AE-62FC-4E71-8D0E-0ACEE5259DEA@yahoo.com>
If you just want to test, then:
2*pnorm(abs(yi)/sqrt(vi), lower.tail=FALSE) <= .05
will tell you which estimates are significantly different from 0 at alpha=.05 (two-sided), assuming (approximate) normality of the sampling distribution.
Best,
Wolfgang
-----Original Message-----
From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces at r-project.org] On Behalf Of Tommy van Steen
Sent: Tuesday, 25 September, 2018 1:25
To: Cesar Terrer Moreno
Cc: r-sig-meta-analysis at r-project.org
Subject: Re: [R-meta] Significance of the individual effects
Hi Cesar,
I?m not sure why you do the ?exp? bit, as removing that bit gives the right lower limits compared to a simple forest plot produced using the metafor-package.
Your ifelse function will only work if all your effect sizes are positive, so it should work in your example, but you cannot use it to decide whether negative effect sizes are significant or not (You?d need the opposite, whether the yi + upper limit >= 0). If you have many studies, a forest plot where you rank the studies by 95%CI lower limit might be an easier way to inspect significance of all individual studies.
Cheers,
Tommy
> On 24 Sep 2018, at 17:46, Cesar Terrer Moreno <cesar.terrer at me.com> wrote:
>
> 0.189653473