[R-meta] compare multiple "bayesmeta" estimates

Dear Christian,

Would it be wrong for Simon to do the following to find out the
difference: 

dif <- bma2$rposterior(1e3,tau.sample=T)  - 
bma1$rposterior(1e3,tau.sample=T) and then obtain the HDI of dif to
see if it contains 0?

Thank you for your expertise,
Reza Norouzian



On Sun, Dec 27, 2020 at 10:30 AM Simon Harmel <sim.harmel at gmail.com>
wrote:

Thank you very much, Christian. I appreciate it. I know and highly
appreciate the fact that you've put so much effort into making
bayesmeta
faster than the MCMC-based equivalents.

But, I really hope that one day we would be able to see still much
faster
algorithms to enable applying Bayesian meta to large-scale research
efforts.

Once again, thank you very much,
Simon

On Sun, Dec 27, 2020 at 6:00 AM R?ver, Christian <
christian.roever at med.uni-goettingen.de> wrote:

Dear Simon,

yes, there is a way to investigate the difference of the two as

well.

Asking for the difference between the two unknowns (the two mean
parameters) technically means asking for a *convolution* of their
probability distributions. From the "bayesmeta()" output we get

the

probability density functions etc, and from these we can derive

the

convolution. A method to compute the convolution is described

here:

  C. Roever and T. Friede.
  Discrete approximation of a mixture distribution
  via restricted divergence.
  Journal of Computational and Graphical Statistics,
  26(1):217-222, 2017.
  https://doi.org/10.1080/10618600.2016.1276840

and R code is provided in the article's supplemental material.

I attached some R code to show the computations based on the

"metafor"

example.

Cheers,

Christian



On Sat, 2020-12-26 at 13:49 -0600, Simon Harmel wrote:

Dear Christian,

Thank you very much. To be clear, you're suggesting a meta-

analysis

of the subgroup meta-analyses, correct?

Well, in my case, I have way too many subgroups, so there will

be

many pairwise comparisons. I wonder if there is a way to get

the

large posterior samples from each subgroup' summary effect and
subtract it from the large posterior samples from another

subgroup

summary effect etc.?

Perhaps, then we can see if the HDI of the posterior of

difference

includes "0"?

Is this possible and/or reasonable given that my goal is to see

if

one subgroup is "different" from another one or not?

Thank you,
Simon

On Sat, Dec 26, 2020 at 12:38 PM R?ver, Christian <
christian.roever at med.uni-goettingen.de> wrote:

Dear Simon,

you can essentially do an analogous analysis (in two stages)

using

the
"bayesmeta" package. Doing the one-stage meta-regression

approach

is
not (yet) possible with bayesmeta, but it should be possible

via

"rjags" (of required).

For the two-stage approach, we then only need to use a normal
approximation for the results from the 1st-stage analyses and
proceed
from there.

I attached some example R code based on the quoted "metafor"
example.

Cheers,

Christian



On Sat, 2020-12-26 at 10:46 -0600, Simon Harmel wrote:

Hello All,

Using "bayesmeta" package, I want to compare multiple

estimates

of

independent Meta-Analyses (i.e., Subgroups).

In metafor, I know we can do this: (

http://www.metafor-project.org/doku.php/tips:comp_two_independent_estimates

)

But I have fit my models in the "bayesmeta" package, so I

was

wondering how to compare across my "bayesmeta" models?

Thanks,
Simon

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