Please do not respond just to me - always CC the list.
Sorry, what I wrote is nonsense. Apparently, I haven't had enough coffee today.
The F statistic replaces the **Qb** statistic.
QE is the same as Qw.
Best,
Wolfgang
-----Original Message-----
From: Fatih ?elik [mailto:fatihcelik2842 at gmail.com]
Sent: Monday, 20 March, 2023 13:04
To: Viechtbauer, Wolfgang (NP)
Subject: Re: predict error in metafor
In the articles I reviewed, both F and Qw test results are reported
separately (e.g., F(4, 38) = 2.8523, p = .0367; R2 = .170; Qw(38) =
539.9001, p < .001).
If they are the same, why are there different values?
Sincerely?
Fatih ?elik <fatihcelik2842 at gmail.com>, 20 Mar 2023 Pzt, 15:02
tarihinde ?unu yazd?:
In the articles I reviewed, both F and Qw test results are reported
separately (e.g., F(4, 38) = 2.8523, p = .0367; R2 = .170; QW(38) =
539.9001, p < .001).
Sincerely?
Viechtbauer, Wolfgang (NP)
<wolfgang.viechtbauer at maastrichtuniversity.nl>, 20 Mar 2023 Pzt, 14:54
tarihinde ?unu yazd?:
The F-test replaces the Qw statistic when using test="knha" (it tests the
same thing, but now based on the K&H method).
-----Original Message-----
From: Fatih ?elik [mailto:fatihcelik2842 at gmail.com]
Sent: Monday, 20 March, 2023 12:23
To: Viechtbauer, Wolfgang (NP); R Special Interest Group for Meta-Analysis
Subject: Ynt: predict error in metafor
Hello, sir.
As you pointed out, when I run the Knapp-Hartung test, Qw (statistic
for testing the model misspecification) does not appear in the output.
How can I access this value? Below I first present to you the model I
created and then the output.
Model:
res1 <- rma(measure="ARAW", ai=ai, mi=mi, ni=ni, mods = ~ sample,
test="knha", data=dat)
outputs:
Mixed-Effects Model (k = 85; tau^2 estimator: REML)
tau^2 (estimated amount of residual heterogeneity): 0.0021 (SE = 0.0004)
tau (square root of estimated tau^2 value): 0.0457
I^2 (residual heterogeneity / unaccounted variability): 94.01%
H^2 (unaccounted variability / sampling variability): 16.70
R^2 (amount of heterogeneity accounted for): 0.00%
Test for Residual Heterogeneity:
QE(df = 83) = 2139.6714, p-val < .0001
Test of Moderators (coefficient 2):
F(df1 = 1, df2 = 83) = 0.9652, p-val = 0.3287
Model Results:
estimate se tval df pval ci.lb ci.ub
intrcpt 0.8286 0.0102 81.0985 83 <.0001 0.8083 0.8489 ***
samplestudent -0.0117 0.0119 -0.9825 83 0.3287 -0.0354 0.0120
---
Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1
---
Yours sincerely?
Kimden: Viechtbauer, Wolfgang (NP)
G?nderilme: 18 Mart 2023 Cumartesi 15:57
Kime: Fatih ?EL?K; R Special Interest Group for Meta-Analysis
Konu: RE: predict error in metafor
When fitting the model, use rma(..., test="knha").
P.S.: Please post in plain text, as explained here: