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Currently, metaBMA by default returns mean + HDIs:
library(metaBMA)
#> Loading required package: Rcpp#> This is metaBMA version 0.6.6#> - Default priors were changed in version 0.6.6.#> - Since default priors may change again, it is safest to specify priors (even when using the defaults).
data(towels)
set.seed(123)
mb<- meta_bma(logOR, SE, study, towels)
#> Warning: There were 2 divergent transitions after warmup. See#> http://mc-stan.org/misc/warnings.html#divergent-transitions-after-warmup#> to find out why this is a problem and how to eliminate them.#> Warning: Examine the pairs() plot to diagnose sampling problemsmb$estimates#> mean sd 2.5% 50% 97.5% hpd95_lower#> averaged 0.2145214 0.0882580 0.03546521 0.2165312 0.3813311 0.03963277#> fixed 0.2208839 0.0783599 0.06556325 0.2219074 0.3747273 0.06047198#> random 0.1988286 0.1062576 -0.02208767 0.2023509 0.3949067 -0.01460747#> hpd95_upper n_eff Rhat#> averaged 0.3846720 NA NA#> fixed 0.3662384 3485.5 1#> random 0.3995670 5359.7 1
But I was wondering if you would be willing to support two additional arguments:
centrality: The point-estimate (centrality index) to compute. Character (vector) of one of these options: "median", "mean" (current default), or "MAP".
Note that the "ETI" ist already available by providing the 2.5% and 97.5% quantiles, similarly as the "median". So only the MAP and SI are missing.
Adding these options could be useful, even though the results should usually be quite similar as long as the posterior is somewhat symmetric. However, since the package uses two approaches to obtaining estimates (integral and stan) it would require some time to implement this. I will put it on the to-do list but this could take quite a while.
Currently,
metaBMA
by default returnsmean
+HDI
s:Created on 2021-01-15 by the reprex package (v0.3.0)
Session info
But I was wondering if you would be willing to support two additional arguments:
"median"
,"mean"
(current default), or"MAP"
."HDI"
,"ETI"
(https://easystats.github.io/bayestestR/reference/eti.html), or"SI"
(https://easystats.github.io/bayestestR/reference/si.html).The text was updated successfully, but these errors were encountered: