[R-meta] predict error in metafor

[Viechtbauer, Wolfgang (NP)]

Yes.

>-----Original Message-----
>From: Fatih Çelik [mailto:fatihcelik2842 using gmail.com]
>Sent: Monday, 20 March, 2023 13:16
>To: Viechtbauer, Wolfgang (NP)
>Cc: R Special Interest Group for Meta-Analysis
>Subject: Re: predict error in metafor
>
>In this case I will report the following values for Qw. Is that correct sir?
>
>Test for Residual Heterogeneity:
>QE(df = 81) = 2339.8382, p-val < .0001
>
>Sincerely…
>
>Viechtbauer, Wolfgang (NP)
><wolfgang.viechtbauer using maastrichtuniversity.nl>, 20 Mar 2023 Pzt, 15:10
>tarihinde şunu yazdı:
>>
>> 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