adding informed priors (from BayesTools) + BMA in Medicine vignette

.gitignore

@@ -15,3 +15,5 @@ Meta
 RoBMA.Rcheck
 .Rhistory
 .Rprofile
+/doc/
+/Meta/

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: RoBMA
 Title: Robust Bayesian Meta-Analyses
-Version: 2.1.0
+Version: 2.1.1
 Maintainer: František Bartoš <[email protected]>
 Authors@R: c( 
     person("František", "Bartoš",     role = c("aut", "cre"),
@@ -40,7 +40,7 @@ NeedsCompilation: yes
 Depends:
     R (>= 4.0.0)
 Imports:
-    BayesTools (>= 0.1.2),
+    BayesTools (>= 0.1.3),
     runjags,
     bridgesampling,
     rjags,

NAMESPACE

@@ -35,6 +35,7 @@ export(plot_models)
 export(prior)
 export(prior_PEESE)
 export(prior_PET)
+export(prior_informed)
 export(prior_none)
 export(prior_weightfunction)
 export(pwnorm)

NEWS.md

@@ -1,3 +1,13 @@
+## version 2.1.1
+### Fixes
+- incorrectly formatted citations in vignettes and capitalization
+
+### Features
+- adding `informed_prior()` function (from the BayesTools package) that allows specification of various informed prior distributions from the field of medicine and psychology
+- adding a vignette reproducing the example of dentine sensitivity with the informed Bayesian model-averaged meta-analysis from Bartoš et al., 2021 ([open-access](https://onlinelibrary.wiley.com/doi/10.1002/sim.9170)),
+- further reductions of fitted object size when setting `save = "min"`
+
+
 ## version 2.1
 ### Fixes
 - more informative error message when the JAGS module fails to load

R/RoBMA-package.R

@@ -17,8 +17,9 @@
 ##' methodology.
 ##'
 ##' More details regarding customization of the model ensembles are provided in the
-##' \href{../doc/ReproducingBMA.html}{\bold{Reproducing BMA}} and
-##' \href{../doc/CustomEnsembles.html}{\bold{Fitting custom meta-analytic ensembles}}
+##' \href{../doc/ReproducingBMA.html}{\bold{Reproducing BMA}},
+##' \href{../doc/MedicineBMA.html}{\bold{BMA in Medicine}}, and
+##' \href{../doc/CustomEnsembles.html}{\bold{Fitting Custom Meta-Analytic Ensembles}}
 ##' vignettes. Please, use the "Issues" section in the GitHub repository to ask any
 ##' further questions.
 ##'

R/data.R

@@ -1,4 +1,4 @@
-#' @title 27 experimental studies from from
+#' @title 27 experimental studies from
 #' \insertCite{anderson2010violent;textual}{RoBMA} that meet the best practice criteria
 #'
 #' @description The data set contains correlation coefficients, sample
@@ -16,7 +16,7 @@
 "Anderson2010"
 
 
-#' @title 9 experimental studies from from
+#' @title 9 experimental studies from
 #' \insertCite{bem2011feeling;textual}{RoBMA} as described in
 #' \insertCite{bem2011must;textual}{RoBMA}
 #'
@@ -32,3 +32,22 @@
 #' @references
 #' \insertAllCited{}
 "Bem2011"
+
+
+#' @title 5 studies with a tactile outcome assessment from
+#' \insertCite{poulsen2006potassium;textual}{RoBMA} of the effect of potassium-containing toothpaste
+#' on dentine hypersensitivity
+#'
+#' @description The data set contains Cohen's d effect sizes, standard errors,
+#' and labels for 5 studies assessing the tactile outcome from a meta-analysis of
+#' the effect of potassium-containing toothpaste on dentine hypersensitivity
+#' \insertCite{poulsen2006potassium}{RoBMA} which was used as an example in
+#' \insertCite{bartos2021bayesian;textual}{RoBMA}.
+#'
+#' @format A data.frame with 3 columns and 5 observations.
+#'
+#' @return a data.frame.
+#'
+#' @references
+#' \insertAllCited{}
+"Poulsen2006"

R/main.R

@@ -297,6 +297,7 @@ RoBMA <- function(
   ### remove model posteriors if asked to
   if(save == "min"){
     object <- .remove_model_posteriors(object)
+    object <- .remove_model_margliks(object)
   }
 
 
@@ -499,6 +500,7 @@ update.RoBMA <- function(object, refit_failed = TRUE,
   ### remove model posteriors if asked to
   if(save == "min"){
     object <- .remove_model_posteriors(object)
+    object <- .remove_model_margliks(object)
   }
 
   return(object)

R/priors.R

@@ -18,9 +18,17 @@ prior_PET  <- BayesTools::prior_PET
 #' @export
 prior_PEESE <- BayesTools::prior_PEESE
 
-
 #' @name prior_weightfunction
 #' @inherit BayesTools::prior_weightfunction
 #' @export
 prior_weightfunction <- BayesTools::prior_weightfunction
 
+#' @name prior_informed
+#' @inherit BayesTools::prior_informed
+#' @details Further details can be found in \insertCite{erp2017estimates;textual}{RoBMA},
+#' \insertCite{gronau2017bayesian;textual}{RoBMA}, and
+#' \insertCite{bartos2021bayesian;textual}{RoBMA}.
+#' @references
+#' \insertAllCited{}
+#' @export
+prior_informed <- BayesTools::prior_informed

R/tools.R

@@ -17,7 +17,7 @@ check_RoBMA <- function(fit){
 
 .is_model_constant         <- function(priors){
   # checks whether there is at least one non-nill prior
-  return(all(sapply(priors, function(prior)is.prior.point(prior) | is.prior.none(prior))) & is.null(priors[["omega"]]))
+  return(all(sapply(priors, function(prior) is.prior.point(prior) | is.prior.none(prior))) & is.null(priors[["omega"]]))
 }
 .remove_model_posteriors   <- function(object){
   for(i in seq_along(object[["models"]])){
@@ -27,6 +27,17 @@ check_RoBMA <- function(fit){
   }
   return(object)
 }
+.remove_model_margliks     <- function(object){
+  for(i in seq_along(object[["models"]])){
+    if(inherits(object$models[[i]][["marglik"]], "bridge")){
+      object$models[[i]]$marglik[["q11"]] <- NULL
+      object$models[[i]]$marglik[["q12"]] <- NULL
+      object$models[[i]]$marglik[["q21"]] <- NULL
+      object$models[[i]]$marglik[["q22"]] <- NULL
+    }
+  }
+  return(object)
+}
 .print_errors_and_warnings <- function(object, max_print = 5){
 
   errors_and_warnings <- .collect_errors_and_warnings(object, max_print = max_print)

inst/REFERENCES.bib

@@ -6,7 +6,7 @@ @article{anderson2010violent
 	journal = {Psychological Bulletin},
 	year    = {2010},
 	pages   = {151},
-	url     = {https://doi.org/10.1037/a0018251}
+	doi     = {10.1037/a0018251}
 }
 
 @article{gronau2017bayesian,
@@ -18,15 +18,19 @@ @article{gronau2017bayesian
   pages     = {123--138},
   year      = {2017},
   publisher = {Taylor \& Francis},
-  url       = {https://doi.org/10.1080/23743603.2017.1326760}
+  doi       = {10.1080/23743603.2017.1326760}
 }
 
 @article{gronau2020primer,
 	title        = {A primer on {B}ayesian model-averaged meta-analysis},
-	author       = {Gronau, Quentin Frederik and Heck, Daniel W and Berkhout, Sophie W and Haaf, Julia M and Wagenmakers, Eric-Jan},
+	author       = {Gronau, Quentin F and Heck, Daniel W and Berkhout, Sophie W and Haaf, Julia M and Wagenmakers, Eric-Jan},
   journal      = {Advances in Methods and Practices in Psychological Science},
-  year         = {in press},
-	url          = {https://doi.org/10.31234/osf.io/97qup}
+  volume       = {4},
+  number       = {3},
+  pages        = {25152459211031256},
+  year         = {2021},
+  publisher    = {SAGE Publications Sage CA: Los Angeles, CA},
+	doi          = {10.1177/25152459211031256}
 }
 
 @article{erp2017estimates,
@@ -37,15 +41,15 @@ @article{erp2017estimates
   number    = {1},
   year      = {2017},
   publisher = {Ubiquity Press},
-  url       = {https://doi.org/10.5334/jopd.33}
+  doi       = {10.5334/jopd.33}
 }
 
 @article{maier2020robust,
 	title        = {Robust {B}ayesian Meta-Analysis: Addressing Publication Bias with Model-Averaging},
 	author       = {Maier, Maximilian and Barto{\v{s}}, Franti{\v{s}}ek and Wagenmakers, Eric-Jan},
 	year         = {in press},
 	journal      = {Psychological Methods},
-	url          = {https://doi.org/10.31234/osf.io/u4cns}
+	doi          = {10.31234/osf.io/u4cns}
 }
 
 
@@ -55,16 +59,16 @@ @unpublished{bartos2021no
   year      = {2021},
   publisher = {PsyArXiv},
   note      = {preprint at \url{https://doi.org/10.31234/osf.io/kvsp7}},
-  url       = {https://doi.org/10.31234/osf.io/kvsp7}
+  doi       = {10.31234/osf.io/kvsp7}
 }
 
 @unpublished{bartos2020adjusting,
-  title     = {Adjusting for Publication Bias in {JASP} — Selection Models and Robust {B}ayesian Meta-Analysis},
-  author    = {Barto{\v{s}}, Franti{\v{s}}ek and Maier, Maximilian and Wagenmakers, Eric-Jan},
-  year      = {2020},
+  title     = {Adjusting for publication bias in {JASP} & {R} -- selection models, {PET-PEESE}, and robust {B}ayesian meta-analysis},
+  author    = {Barto{\v{s}}, Franti{\v{s}}ek and Maier, Maximilian and Quintana, Daniel S and Wagenmakers, Eric-Jan},
+  year      = {2021},
   journal   = {PsyArXiv},
   note      = {preprint at \url{https://doi.org/10.31234/osf.io/75bqn}},
-  url       = {https://doi.org/10.31234/osf.io/75bqn}
+  doi       = {10.31234/osf.io/75bqn}
 }
 
 @misc{jasp14,
@@ -83,7 +87,7 @@ @article{bem2011feeling
   pages     = {407},
   year      = {2011},
   publisher = {American Psychological Association},
-  url       = {https://doi.org/10.1037/a0021524}
+  doi       = {10.1037/a0021524}
 }
 
 @article{bem2011must,
@@ -95,7 +99,7 @@ @article{bem2011must
   number    = {4},
   pages     = {716},
   year      = {2011},
-  url       = {https://doi.org/10.1037/a0024777}
+  doi       = {10.1037/a0024777}
 }
 
 @article{wagenmakers2011why,
@@ -106,7 +110,7 @@ @article{wagenmakers2011why
   volume    = {100},
   number    = {3},
   pages     = {426--432},
-  url       = {https://doi.org/10.1037/a0022790}
+  doi       = {10.1037/a0022790}
 }
 
 @article{rouder2011bayes,
@@ -118,7 +122,7 @@ @article{rouder2011bayes
   pages     = {682--689},
   year      = {2011},
   publisher = {Springer},
-  url       = {https://doi.org/10.3758/s13423-011-0088-7}
+  doi       = {10.3758/s13423-011-0088-7}
 }
 
 @misc{schimmack2018my,
@@ -136,3 +140,56 @@ @book{borenstein2011introduction
   year      = {2011},
   publisher = {John Wiley \& Sons}
 }
+
+@article{bartos2021bayesian,
+  title     = {Bayesian model-averaged meta-analysis in medicine},
+  author    = {Barto{\v{s}}, Franti{\v{s}}ek and Gronau, Quentin F and Timmers, Bram and Otte, Willem M. and Ly, Alexander and Wagenmakers, Eric-Jan},
+  journal   = {Statistics in Medicine},
+  doi       = {10.1002/sim.9170},
+  year      = {2021}
+}
+
+@article{poulsen2006potassium,
+  title     = {Potassium containing toothpastes for dentine hypersensitivity},
+  author    = {Poulsen, Sven and Errboe, Marie and Mevil, Yamila Lescay and Glenny, Anne-Marie},
+  journal   = {Cochrane Database of Systematic Reviews},
+  number    = {3},
+  year      = {2006},
+  doi       = {10.1002/14651858.cd001476.pub2},
+  publisher = {John Wiley \& Sons, Ltd}
+}
+
+@article{stanley2014meta,
+  title        = {Meta-regression approximations to reduce publication selection bias},
+  author       = {Stanley, Tom D and Doucouliagos, Hristos},
+  journal      = {Research Synthesis Methods},
+  volume       = {5},
+  number       = {1},
+  pages        = {60--78},
+  year         = {2014},
+  publisher    = {Wiley Online Library},
+  doi          = {10.1002/jrsm.1095}
+}
+
+@article{stanley2017limitations,
+  title        = {Limitations of {PET-PEESE} and other meta-analysis methods},
+  author       = {Stanley, Tom D},
+  journal      = {Social Psychological and Personality Science},
+  volume       = {8},
+  number       = {5},
+  pages        = {581--591},
+  year         = {2017},
+  publisher    = {Sage Publications Sage CA: Los Angeles, CA},
+  doi          = {10.1177/1948550617693062}
+}
+
+@article{vevea1995general,
+	title        = {A general linear model for estimating effect size in the presence of publication bias},
+	author       = {Vevea, Jack L and Hedges, Larry V},
+	year         = 1995,
+	journal      = {Psychometrika},
+	volume       = 60,
+	number       = 3,
+	pages        = {419--435},
+	doi          = {10.1007/BF02294384}
+}