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[R-meta] Subgroup analysis with RVE

5 messages · Ioana Cristea, Wolfgang Viechtbauer, Gerta Ruecker

Wolfgang Viechtbauer
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Dear Ioana,

I am not sure why you think that a test of that moderators is not useful when the number of effect sizes is so different between the two groups. All else equal, power will indeed be lower as opposed to the case where k is similar for the two groups, but that will be the case no matter how you analyze the data (via meta-regression or subgrouping).

This aside, I am a bit confused by your question. A subgroup analysis is just that: Fitting a particular model in a subgroup of the studies. That can be done with or without RVE. You seem to have done this already ("I estimated effects in the high and low subgroup separately").

Best,
Wolfgang
Ioana Cristea
# 
Hi
Thank you, sorry I did not explain clearly. I estimated effects within
subgroups with RVE (intercept only model in each), but I did not do a
between-groups test of significance. I did fit a model with a between
groups covariate (subgroups coded dichotomously: high/low), which I took to
be the equivalent of a meta-regression with a dichotomous predictor.
Best
Ioana

On Thu, Dec 3, 2020 at 9:20 AM Viechtbauer, Wolfgang (SP) <
wolfgang.viechtbauer at maastrichtuniversity.nl> wrote:

            

      
      
      
    

        

  
    

      
      
    

  


  


      

    

    

      
      

        


  

        

      Wolfgang Viechtbauer
    

    

      
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Yes, adding this variable as a covariate is indeed meta-regression with a dichotomous predictor. This assumes that the amount of heterogeneity is the same within the two subgroups. If you subgroup, then you automatically allow the amount of heterogeneity to differ between the two groups. This is discussed here:

http://www.metafor-project.org/doku.php/tips:comp_two_independent_estimates

When combining this with RVE, things are a bit different though. RVE doesn't make assumptions about the underlying variance structure (in fact, the whole point of RVE is that it works (asymptotically) even if the var-cov structure is misspecified). So, even if tau^2 differs across the two groups, RVE in the context of a meta-regression model is still going to provide valid inferences.

Best,
Wolfgang

            

      
      
      
    

  
  


  


      

    

    

      
      

        


  

        

      Gerta Ruecker
    

    

      
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Dear Wolfgang, dear Ioana,

This is only to hint to a different use of the notion "subgroup 
analysis" at Cochrane, which may have led to misunderstandings here. 
Cochrane uses "subgroup analysis" to denote metaregression with a 
nominal covariate (common heterogeneity parameter and between-groups 
test), not for separate analyses within groups. See the Cochrane 
Handbook for Systematic Reviews of Interventions, 
https://training.cochrane.org/handbook/current/chapter-10#section-10-11-2 
. Thus, Cochrane's subgroup analysis is a special case of 
metaregression. This notion is also used in R package meta.

Best,

Gerta


Am 03.12.2020 um 10:10 schrieb Viechtbauer, Wolfgang (SP):

            

      
      
      
    

        

      
      
    

  
  


  


      

    

    

      
      

        


  

        

      Wolfgang Viechtbauer
    

    

      
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Hi Gerta,

Interesting, thanks for this clarification on terminology.

In principle, it is an arbitrary distinction anyway, since one can easily fit a meta-regression model that allows tau^2 to differ across subgroups, which is exactly identical to fitting RE models in the two subgroups.

But this is only true when the only predictor is the factor distinguishing the subgroups. Once the model includes additional predictors, the equivalence breaks down (unless one fits a model that allows the coefficients for the additional predictors to also differ across subgroups).

Best,
Wolfgang