[R-meta] Compiling different design in the same met-analysis

[Viechtbauer, Wolfgang (SP)]

You can do a likelihood ratio test. Using the same example:

library(metafor)
dat <- escalc(measure="RR", ai=tpos, bi=tneg, ci=cpos, di=cneg, data=dat.bcg)
dat$alloc <- ifelse(dat$alloc == "random", "random", "other")
res1 <- rma.mv(yi, vi, mods = ~ alloc, random = ~ alloc | trial, struct="DIAG", data=dat, digits=3)
res0 <- rma.mv(yi, vi, mods = ~ alloc, random = ~ alloc | trial, struct="ID", data=dat, digits=3)
anova(res1, res0)

The issue you mention at the end is not relevant here, since we are testing H0: tau^2_1 = tau^2_2, not something like H0: tau^2 = 0. In the latter case, the parameter is at the boundary of the parameter space under the null hypothesis, which leads to the issue you mention.

Best,
Wolfgang

>-----Original Message-----
>From: Philippe Tadger [mailto:philippetadger using gmail.com]
>Sent: Tuesday, 04 May, 2021 12:52
>To: Viechtbauer, Wolfgang (SP); r-sig-meta-analysis using r-project.org
>Subject: Re: [R-meta] Compiling different design in the same met-analysis
>
>Thanks Wolfgang!, simple and elegant explanation in your post.
>
>Is it possible to check which assumption fit better the data (same variance vs
>different variance in each subgroup)?
>
>The option "different variance" is more general than "same variance". So, is it
>possible to say that they are nested and do an ANOVA between them?
>
>I wonder if for such "variance test" the usual chi2 distribution doesn't apply,
>and require a mixture of chi2, as it has been propose previously when the test for
>RE variance are conducted.
>
>On 04/05/2021 12:14, Viechtbauer, Wolfgang (SP) wrote:
>If one runs separate meta-analyses, one can also test for subgroup differences.
>This is not a distinguishing characteristic. The main difference is that separate
>meta-analyses automatically allow all parameters (including any variance
>components) to differ across analyses, while a single meta-regression model (with
>a categorical moderator) will by default assume that all parameters except of
>course for the subgroup means are the same across subgroups. But even this
>assumption can be relaxed and one can fit a meta-regression model that will give
>you exactly identical results as fitting separate meta-analyses within subgroups.
>See here:
>
>https://www.metafor-project.org/doku.php/tips:comp_two_independent_estimates
>
>The same idea generalizes to models such as those that can be fitted with
>rma.mv().
>
>Best,
>Wolfgang
>
>-----Original Message-----
>From: R-sig-meta-analysis [mailto:r-sig-meta-analysis-bounces using r-project.org] On
>Behalf Of Philippe Tadger
>Sent: Tuesday, 04 May, 2021 12:04
>To: r-sig-meta-analysis using r-project.org
>Subject: Re: [R-meta] Compiling different design in the same met-analysis
>
>Thanks Gerta for such a simple and important reminder.
>
>Apart from having test for subgroup differences, which other advantage
>can have doing a subgroup analysis (with the moderator in
>meta-regression) vs separate meta-analyses?
>Just assuming that is a categorical moderator