[R-meta] Wald_test error

James Pustejovsky jepu@to @end|ng |rom gm@||@com
Sun Aug 15 04:37:58 CEST 2021

Please keep the list cc'd. Responses below.


On Fri, Aug 13, 2021 at 9:56 AM Cátia Ferreira De Oliveira <
cmfo500 using york.ac.uk> wrote:

> Dear James,
> Thank you for your reply! I wasn't able to find any examples similar to
> mine, so could you give me an idea of how one would go about doing the
> constraints when you want to test for an overall group effect and there's
> an interaction term?
> group <- robu(formula = yi ~ 0 + Group + Component:Group, data = Data,
> studynum = Study, var.eff.size = vi,
>                        rho = .8, small = TRUE)
> print(group)

To answer this question, we need to know what the null hypothesis of
interest is. In the model as you've specified it, the definition of the
group effects depends on how you specify the contrasts for the Component
term. As a result, it's not clear what the main effects of the Group term
mean. Could state in words what hypothesis you're trying to test?

> Also, just to confirm, if there is only one predictor with three levels
> (yi ~ 0 + Variable), would the constraints be the following:
> Wald_test(model, constraints = matrix(c(1,0,0,0,1,0,0,0,1),3,3), vcov =
> "CR2")
> Again, we need to know what the null hypothesis of interest is. Using a
diagonal constraint matrix (as you've specified) will test the null that
the average effect size is equal to zero for each of three levels of
Variable. That might be of interest, or perhaps you instead want to test
whether the average effect sizes are *identical* across the three levels of
Variable (but not necessarily all zero). For the latter null, you would
instead use

constraints = constrain_equal(1:3)


constraints = constrain_equal("Variable", reg_ex = TRUE)

	[[alternative HTML version deleted]]

More information about the R-sig-meta-analysis mailing list