attempt at matching metafor results with glmmTMB

xmeta.R

library(brms)
library(metafor)
library(broom)
library(broom.mixed)

set.seed(101)
y <- rnorm(10)
sei <- rgamma(10, shape = 1)

## metafor: fixed-effect meta-analysis
mf1 <- rma(y, sei = sei, method = "FE")

## glmmTMB:
## fix all dispersions (standard errors) to known values
## note that we have to specify `betad` as log VARIANCES not 
##  log SDs (see https://github.com/glmmTMB/glmmTMB/issues/955) --
##  this may change in the future
library(glmmTMB)
dd <- data.frame(y, sei, id = factor(1:10))
gt1 <- glmmTMB(y ~ 1, 
               ## different SD value for each `id`
               dispformula = ~0+id,
               data = dd,
               ## fix SDs, don't estimate them
               map = list(betad = factor(rep(NA,10))),
               ## specify SD values (actually variances)
               start = list(betad = 2*log(dd$sei)))


## brms equivalent
br1 <- brm(y | se(sei) ~ 1, data = dd)

(list(glmmTMB = gt1, brms = br1, metafor = mf1)
    |> purrr::map_dfr(tidy, .id = "pkg")
    |> dplyr::filter(is.na(effect) | effect == "fixed")
    |> dplyr::select(pkg, estimate, std.error)
)

##   pkg     estimate std.error
## 1 glmmTMB    0.898    0.0389
## 2 brms       0.898    0.0399
## 3 metafor    0.898    0.0389