[R-meta] predict error in metafor

[Viechtbauer, Wolfgang (NP)]

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 Çelik [mailto:fatihcelik2842 using 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 Çelik <fatihcelik2842 using gmail.com>, 20 Mar 2023 Pzt, 15:02
>tarihinde şunu yazdı:
>>
>> 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 using maastrichtuniversity.nl>, 20 Mar 2023 Pzt, 14:54
>> tarihinde şunu yazdı:
>> >
>> > The F-test replaces the Qw statistic when using test="knha" (it tests the
>same thing, but now based on the K&H method).
>> >
>> > Best,
>> > Wolfgang
>> >
>> > >-----Original Message-----
>> > >From: Fatih Çelik [mailto:fatihcelik2842 using 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)
>> > >Gönderilme: 18 Mart 2023 Cumartesi 15:57
>> > >Kime: Fatih ÇELİK; 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:
>> > >
>> > >https://stat.ethz.ch/mailman/listinfo/r-sig-meta-analysis
>> > >
>> > >Best,
>> > >Wolfgang