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
[R-meta] compare multiple "bayesmeta" estimates
5 messages · Simon Harmel, Röver, Christian
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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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: (
) But I have fit my models in the "bayesmeta" package, so I was wondering how to compare across my "bayesmeta" models? Thanks, Simon
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: (
) 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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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: (
) But I have fit my models in the "bayesmeta" package, so I was wondering how to compare across my "bayesmeta" models? Thanks, Simon