[R-meta] F test vs QM test for test of moderators

[Michael Dewey]

Hello Huang

You asked it to do individual tests with the t distribution not the 
normal and in that case the omnibus test is done with the F not 
chi-square. This is mentioned in the help for rma.mv in the section on 
Tests and Confidence Intervals.

Michael

On 29/04/2023 16:06, Huang Wu via R-sig-meta-analysis wrote:
> Hi Yefeng,
> 
> Thank you very much for your reply.
> 
> In other examples on the metafor package website, the results of Test of
> Moderators are QM values (e.g., *QM*(df = 3) = 15.9842, p-val = 0.0011) but
> mine was F values. I wonder if the QM test was based on chi-square
> distribution, and the reason that causes this difference. I would highly
> appreciate your feedback.
> 
> Best regards,
> Huang
> 
> 
> 
> 
> On Sat, Apr 29, 2023 at 12:49 AM Yefeng Yang <yefeng.yang1 using unsw.edu.au>
> wrote:
> 
>> Dear Huang
>>
>> If you understand what QM test is, it is not difficult to find out "Test
>> of Moderators (coefficients 2:3)" printed below your output is the QM test
>> results. Your test statistic was tested against F distribution. You can
>> also use chi-square distribution (but not recommended). In essence, QM
>> test is a sort of omnibus test or joint null-hypothesis test.
>>
>> Best,
>> Yefeng
>>
>>
>> ------------------------------
>> *From:* R-sig-meta-analysis <r-sig-meta-analysis-bounces using r-project.org>
>> on behalf of Huang Wu via R-sig-meta-analysis <
>> r-sig-meta-analysis using r-project.org>
>> *Sent:* Saturday, 29 April 2023 12:34
>> *To:* R meta <r-sig-meta-analysis using r-project.org>
>> *Cc:* Huang Wu <wuhuang0421 using gmail.com>
>> *Subject:* [R-meta] F test vs QM test for test of moderators
>>
>> Dear all,
>>
>> I am writing to ask about the Test of Moderators in meta-analysis.
>> Specifically, I am curious about the appropriate test to use between the F
>> test and QM test. I ran the following code and obtained results using the F
>> test for the Test of Moderators. However, I would like to explore how to
>> obtain QM test results.
>>
>> Could you kindly advise me on the suitable test to use and how to obtain QM
>> test results using the metafor package?
>>
>> Thank you for your assistance.
>> Huang
>> ----------------------------------------------------
>>
>> USnew_c.Dnoctl.model <- rma.mv(yi=effect_d, #effect size
>>                                 V = VUSnew_c.Dnoctl, #variance (tHIS IS WHAt
>> CHANGES FROM HEmodel)
>>                                 mods = ~ grade_level,
>>                                 random = ~1 | ID/eid, #nesting structure
>>                                 test= "t", #use t-tests
>>                                 data=USnew_c.Dnoctl, #define data
>>                                 method="REML") #estimate variances using
>> REML
>>
>> summary(USnew_c.Dnoctl.model)
>>
>> ----------------------------------------------------
>> Multivariate Meta-Analysis Model (k = 142; method: REML)
>>
>>    logLik  Deviance       AIC       BIC      AICc
>>   16.9680  -33.9361  -23.9361   -9.2637  -23.4849
>>
>> Variance Components:
>>
>>              estim    sqrt  nlvls  fixed  factor
>> sigma^2.1  0.0300  0.1733     19     no      ID
>> sigma^2.2  0.0161  0.1270    142     no  ID/eid
>>
>> Test for Residual Heterogeneity:
>> QE(df = 139) = 344.3018, p-val < .0001
>>
>> Test of Moderators (coefficients 2:3):
>> F(df1 = 2, df2 = 139) = 1.1327, p-val = 0.3251
>>
>>          [[alternative HTML version deleted]]
>>
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-- 
Michael
http://www.dewey.myzen.co.uk/home.html