[R-meta] Specifying the random effect structure of our multilevel meta-analysis in metafor

James Pustejovsky jepu@to @end|ng |rom gm@||@com
Mon Jan 23 23:42:15 CET 2023

Hi Paco,

Responses below.


On Mon, Jan 23, 2023 at 4:25 PM Tomas-Valiente Jorda Francisco <
tomasf using student.ethz.ch> wrote:

> One clarification question on the RVE approach you suggest. Your proposal
> is that (as per the code below) we estimate our model with metafor::rma.mv
> using some assumed variance-covariance matrix and that for hypothesis
> testing we use clubSandwich's coef_test or coef_int or Wald_test, right?
> Or did I misunderstand you?
> V2 <- impute_covariance_matrix(vi=diag(V), cluster=df$experiment, r=0.6)
> model <- rma.mv(effect, random = list(~ 1 | experiment / voting_prop, ~ 1
> | arm.in.experiment), data = df, V = V2, mods = ~ voting_prop)
> coef_test(model, vcov="CR2")
Correct. You can also accomplish the same thing using the metafor::robust()
function, which calls clubSandwich under the hood:

model_robust <- robust(model, cluster = experiment, clubSandwich = TRUE)

For tests of hypotheses involving multiple parameters, you'll still need to
use clubSandwich::Wald_test() or wildmeta::Wald_test_cwb().

	[[alternative HTML version deleted]]

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