[R-meta] Welcome to the "R-sig-meta-analysis" mailing list

Viechtbauer Wolfgang (SP) wolfgang.viechtbauer at maastrichtuniversity.nl
Mon Oct 16 17:32:05 CEST 2017

Dear Anne-Wil,

You are mixing up two things:

1) The unbiased estimate of the variance is

var(x) = sum((x - mean(x))^2) / (n-1).

2) The variance of a mean is

var(x) / n

So, the correct computation is

vi <- sdi^2/ni

(assuming that sdi is the square-root of the unbiased estimate of the variance, but this is pretty much what is always reported).


-----Original Message-----
From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces at r-project.org] On Behalf Of Anne-Wil Kruijt
Sent: Monday, 16 October, 2017 17:20
To: r-sig-meta-analysis at r-project.org
Subject: Re: [R-meta] Welcome to the "R-sig-meta-analysis" mailing list

Apologies, where I wrote ‘method = “MN”’, it should have been ‘measure = “MN”’.

On 16/10/2017, 17:18, "Anne-Wil Kruijt" <mail at awkruijt.nl> wrote:

    Dear all,
    Thank you, professor Viechtbauer, for referring me to this list. 
    Delving into metafor’s mechanics I noticed that when ‘method = “MN” ‘ is specified in escalc(), its calculation of sampling variance (vi) is “vi <- sdi^2/ni”. I wondered why there is no option to use the(/a?) unbiased estimator “vi <- sdi^2/ni-1”. I’m considered to bypass the escalc step and ‘manually’ compute vi as sdi^2/ni-1 – but I’m hesitant because it isn’t an option in escalc() (when method = “MN”, i.e. when obtaining the ‘raw mean difference’ for input as yi). Does anyone have any insights to share on why it is or is not a good idea to use the ‘unbiased estimator’ in the context of a REML MA on raw mean difference values? 
    All best,

More information about the R-sig-meta-analysis mailing list