effect size information messages + BayesTools 0.2.3 update

.github/workflows/R-CMD-check.yaml

@@ -28,7 +28,7 @@ jobs:
           - {os: ubuntu-20.04,   r: 'release', rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest"}
           - {os: ubuntu-20.04,   r: 'devel',   rspm: "https://packagemanager.rstudio.com/cran/__linux__/focal/latest", http-user-agent: "R/4.1.0 (ubuntu-20.04) R (4.1.0 x86_64-pc-linux-gnu x86_64 linux-gnu) on GitHub Actions" }
         #  - {os: macOS-11.6.2,   r: 'release'} # the release C++ version does not compile properly
-        
+
     env:
       R_REMOTES_NO_ERRORS_FROM_WARNINGS: true
       RSPM: ${{ matrix.config.rspm }}
@@ -83,7 +83,7 @@ jobs:
         run: |
           remotes::install_deps(dependencies = TRUE)
           remotes::install_cran("rcmdcheck")
-          remotes::install_version("BayesTools", "0.1.3")
+          remotes::install_version("BayesTools", "0.2.3")
         shell: Rscript {0}
 
       - name: Check

.github/workflows/R-CMD-tests.yaml

@@ -104,7 +104,7 @@ jobs:
         run: |
           remotes::install_deps(dependencies = TRUE)
           remotes::install_cran("rcmdcheck")
-          remotes::install_version("BayesTools", "0.1.3")
+          remotes::install_version("BayesTools", "0.2.3")
           install.packages("devtools")
           install.packages("testthat")
           install.packages("vdiffr")

.github/workflows/pkgdown.yaml

@@ -77,7 +77,7 @@ jobs:
         run: |
           remotes::install_deps(dependencies = TRUE)
           install.packages("pkgdown")
-          remotes::install_version("BayesTools", "0.1.3")
+          remotes::install_version("BayesTools", "0.2.3")
         shell: Rscript {0}
 
       - name: Install package

.github/workflows/test-coverage.yaml

@@ -26,7 +26,7 @@ jobs:
 
     env:
       GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
-      
+
     steps:
       - uses: actions/checkout@v2
 
@@ -77,7 +77,7 @@ jobs:
           install.packages(c("remotes"))
           remotes::install_deps(dependencies = TRUE)
           remotes::install_cran("covr")
-          remotes::install_version("BayesTools", "0.1.3")
+          remotes::install_version("BayesTools", "0.2.3")
         shell: Rscript {0}
 
       - name: Test coverage

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: RoBMA
 Title: Robust Bayesian Meta-Analyses
-Version: 2.2.0
+Version: 2.2.1
 Maintainer: František Bartoš <[email protected]>
 Authors@R: c( 
     person("František", "Bartoš",     role = c("aut", "cre"),

NEWS.md

@@ -1,3 +1,8 @@
+## version 2.2.1
+### Changes
+- message about the effect size scale of parameter estimates is always shown
+- compatibility with BayesTools 0.2.0+
+
 ## version 2.2
 ### Features
 - three-level meta-analysis by specifying `study_ids` argument in `RoBMA`. However, note that this is (1) an experimental feature and (2) the computational expense of fitting selection models with clustering is extreme. As of now, it is almost impossible to have more than 2-3 estimates clustered within a single study).

R/fit-and-marglik.R

@@ -124,20 +124,21 @@
 
   }else{
 
-    fit_data       <- .fit_data(object[["data"]], priors, add_info[["effect_direction"]], add_info[["prior_scale"]])
-    converged      <- TRUE
-    has_posterior  <- FALSE
-    fit            <- list()
-    class(fit)     <- "null_model"
-    marglik        <- list()
-    marglik$logml  <- sum(stats::dnorm(fit_data[["y"]], priors$mu$parameters[["location"]], fit_data[["se"]], log = TRUE))
-    class(marglik) <- "bridge"
+    fit_data                <- .fit_data(object[["data"]], priors, add_info[["effect_direction"]], add_info[["prior_scale"]])
+    converged               <- TRUE
+    has_posterior           <- FALSE
+    fit                     <- list()
+    attr(fit, "prior_list") <- priors
+    class(fit)              <- "null_model"
+    marglik                 <- list()
+    marglik$logml           <- sum(stats::dnorm(fit_data[["y"]], priors$mu$parameters[["location"]], fit_data[["se"]], log = TRUE))
+    class(marglik)          <- "bridge"
 
   }
 
   # add model summaries
   if(has_posterior){
-    fit_summary   <- BayesTools::runjags_estimates_table(fit = fit, prior_list = priors, warnings = warnings)
+    fit_summary   <- BayesTools::runjags_estimates_table(fit = fit, warnings = warnings)
     if(add_info[["prior_scale"]] != "y"){
       fit_summaries <- .runjags_summary_list(fit, priors, add_info[["prior_scale"]], warnings)
     }else{
@@ -602,7 +603,6 @@
 
     summary_list[[measure]] <- BayesTools::runjags_estimates_table(
       fit             = fit,
-      prior_list      = priors,
       transformations = transformations,
       warnings        = warnings,
       footnotes       = .scale_note(priors_scale, measure),

R/transformations.R

@@ -947,11 +947,10 @@ scale_logOR2d     <- function(logOR) .scale_logOR2d$fun(logOR)
 }
 
 .scale_note <- function(prior_scale, output_scale){
-  if(prior_scale == output_scale){
-    return(NULL)
-  }else{
-    return(paste0("The estimates are summarized on the ", .transformation_names(output_scale)," scale (priors were specified on the ", .transformation_names(prior_scale), " scale)."))
-  }
+  return(sprintf(
+    "The estimates are summarized on the %1$s scale (priors were specified on the %2$s scale).",
+    .transformation_names(output_scale),
+    .transformation_names(prior_scale)))
 }
 
 

R/utilities.R

@@ -76,33 +76,27 @@ assign("max_cores",       parallel::detectCores(logical = TRUE) - 1,  envir = Ro
     return(invisible(FALSE))
   }
 
-  BayesTools_min <- switch(
+  BayesTools_required <- switch(
     paste0(RoBMA.version, collapse = "."),
-    "2.1.1" = "0.1.3",
-    "2.1.2" = "0.1.3",
-    "2.2.0" = "0.1.3",
-    stop("New RoBMA version needs to be defined in '.check_BayesTools' function!")
-  )
-  BayesTools_max <- switch(
-    paste0(RoBMA.version, collapse = "."),
-    "2.1.1" = "0.1.3",
-    "2.1.2" = "0.1.3",
-    "2.2.0" = "0.1.3",
+    "2.1.1" = c("0.1.3", "0.1.3"),
+    "2.1.2" = c("0.1.3", "0.1.3"),
+    "2.2.0" = c("0.1.3", "0.1.3"),
+    "2.2.1" = c("0.2.3", "0.2.999"),
     stop("New RoBMA version needs to be defined in '.check_BayesTools' function!")
   )
 
-  min_OK <- all(as.integer(strsplit(BayesTools_min, ".", fixed = TRUE)[[1]]) <= unlist(BayesTools.version))
-  max_OK <- all(as.integer(strsplit(BayesTools_max, ".", fixed = TRUE)[[1]]) >= unlist(BayesTools.version))
+  min_OK <- all(as.integer(strsplit(BayesTools_required[1], ".", fixed = TRUE)[[1]]) <= unlist(BayesTools.version))
+  max_OK <- all(as.integer(strsplit(BayesTools_required[2], ".", fixed = TRUE)[[1]]) >= unlist(BayesTools.version))
 
   if(min_OK && max_OK){
     return(invisible(TRUE))
   }else{
     warning(sprintf(
       "RoBMA version %1$s requires BayesTools version higher or equal %2$s and lower or equal %3$s.",
       paste0(RoBMA.version, collapse = "."),
-      BayesTools_min,
-      BayesTools_max
-    ), call.=FALSE)
+      BayesTools_required[1],
+      BayesTools_required[2]
+    ), call.= FALSE)
     return(invisible(FALSE))
   }
 }