version bump

CITATION.cff

@@ -9,7 +9,7 @@ type: software
 license: AGPL-3.0-or-later
 title: 'FreesearchR: A free and open-source browser based data analysis tool for researchers
   with publication ready output'
-version: 25.5.4
+version: 25.5.5
 doi: 10.5281/zenodo.14527429
 identifiers:
 - type: url
@@ -990,6 +990,18 @@ references:
     orcid: https://orcid.org/0000-0002-5645-3493
   year: '2025'
   doi: 10.32614/CRAN.package.shinyjs
+- type: software
+  title: emmeans
+  abstract: 'emmeans: Estimated Marginal Means, aka Least-Squares Means'
+  notes: Imports
+  url: https://rvlenth.github.io/emmeans/
+  repository: https://CRAN.R-project.org/package=emmeans
+  authors:
+  - family-names: Lenth
+    given-names: Russell V.
+    email: russell-lenth@uiowa.edu
+  year: '2025'
+  doi: 10.32614/CRAN.package.emmeans
 - type: software
   title: styler
   abstract: 'styler: Non-Invasive Pretty Printing of R Code'

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: FreesearchR
 Title: A free and open-source browser based data analysis tool for researchers with publication ready output
-Version: 25.5.4
+Version: 25.5.5
 Authors@R: c(
     person("Andreas Gammelgaard", "Damsbo",email="agdamsbo@clin.au.dk", role = c("aut", "cre"),
            comment = c(ORCID = "0000-0002-7559-1154")),
@@ -63,7 +63,8 @@ Imports:
     ggforce,
     RcppArmadillo,
     ggcorrplot,
-    shinyjs
+    shinyjs,
+    emmeans
 Suggests: 
     styler,
     devtools,

NEWS.md

@@ -2,6 +2,8 @@
 
 - *FIX* several minor bugs and polish
 
+- *FIX* include/exclude p-values in regression table.
+
 # FreesearchR 25.5.4
 
 - *FIX* correctly omit NAs in `data_type()` call

R/app_version.R

@@ -1 +1 @@
-app_version <- function()'25.5.4'
+app_version <- function()'25.5.5'

R/hosted_version.R

@@ -1 +1 @@
-hosted_version <- function()'v25.5.4-250513'
+hosted_version <- function()'v25.5.5-250514'

R/regression-module.R

@@ -322,7 +322,7 @@ regression_server <- function(id,
 
       ##############################################################################
       #########
-      #########  Regression analysis
+      #########  Regression models
       #########
       ##############################################################################
 
@@ -370,6 +370,179 @@ regression_server <- function(id,
         }
       )
 
+
+
+      shiny::observeEvent(
+        list(
+          data_r(),
+          regression_vars()
+        ),
+        {
+          rv$list$regression$tables <- NULL
+        }
+      )
+
+      ##############################################################################
+      #########
+      #########  Regression table
+      #########
+      ##############################################################################
+
+      ### Creating the regression table
+      shiny::observeEvent(
+        input$load,
+        {
+          shiny::req(rv$list$regression$models)
+          ## To avoid plotting old models on fail/error
+          rv$list$regression$tables <- NULL
+
+          # browser()
+          tryCatch(
+            {
+              parameters <- list(
+                p.values = input$add_regression_p == "no"
+              )
+
+              out <- lapply(rv$list$regression$models, \(.x){
+                .x$model
+              }) |>
+                purrr::map(\(.x){
+                  do.call(
+                    regression_table,
+                    append_list(.x, parameters, "x")
+                  )
+                })
+
+              rv$list$regression$models |>
+                purrr::imap(\(.x, .i){
+                  rv$list$regression$models[[.i]][["code_table"]] <- paste(
+                    .x$code,
+                    expression_string(rlang::call2(.fn = "regression_table", !!!parameters, .ns = "FreesearchR"), assign.str = NULL),
+                    sep = "|>\n"
+                  )
+                })
+
+              rv$list$regression$tables <- out
+              rv$list$input <- input
+            },
+            warning = function(warn) {
+              showNotification(paste0(warn), type = "warning")
+            },
+            error = function(err) {
+              showNotification(paste0("Creating a regression table failed with the following error: ", err), type = "err")
+            }
+          )
+        }
+      )
+
+      ## Consider creating merged table with theming and then passing object
+      ## to render.
+
+      output$table2 <- gt::render_gt({
+        ## Print checks if a regression table is present
+        if (!is.null(rv$list$regression$tables)) {
+          # gtsummary::theme_gtsummary_journal(journal = "jama")
+          merged <- rv$list$regression$tables |>
+            tbl_merge()
+
+          if (input$add_regression_p == "no") {
+            merged <- merged |>
+              gtsummary::modify_column_hide(column = dplyr::starts_with("p.value"))
+          }
+
+          out <- merged |>
+            gtsummary::as_gt() |>
+            gt::tab_header(gt::md(glue::glue("**Table 2: {rv$list$regression$params$descr}**")))
+
+          # rv$list$regression$table_merged <- out
+
+          out
+        } else {
+          return(NULL)
+        }
+      })
+
+      ##############################################################################
+      #########
+      #########  Coefficients plot
+      #########
+      ##############################################################################
+
+      shiny::observeEvent(list(
+        input$plot_model,
+        rv$list$regression
+      ), {
+        shiny::req(input$plot_model)
+
+        tryCatch(
+          {
+            p <- merge_long(
+              rv$list$regression,
+              sort_by(
+                input$plot_model,
+                c("Univariable", "Minimal", "Multivariable"),
+                na.rm = TRUE
+              )
+            ) |>
+              (\(.x){
+                if (length(input$plot_model) > 1) {
+                  plot.tbl_regression(
+                    x = .x,
+                    colour = "model",
+                    dodged = TRUE
+                  ) +
+                    ggplot2::theme(legend.position = "bottom") +
+                    ggplot2::guides(color = ggplot2::guide_legend(reverse = TRUE))
+                } else {
+                  plot.tbl_regression(
+                    x = .x,
+                    colour = "variable"
+                  ) +
+                    ggplot2::theme(legend.position = "none")
+                }
+              })()
+
+            rv$plot <- p +
+              ggplot2::scale_y_discrete(labels = scales::label_wrap(15)) +
+              gg_theme_shiny()
+          },
+          error = function(err) {
+            showNotification(paste0(err), type = "err")
+          }
+        )
+      })
+
+
+      output$regression_plot <- shiny::renderPlot(
+        {
+          shiny::req(input$plot_model)
+
+          rv$plot
+        },
+        alt = "Regression coefficient plot"
+      )
+
+      # plot_download_server(
+      #   id = ns("reg_plot_download"),
+      #   data = shiny::reactive(rv$plot)
+      # )
+
+      output$download_plot <- shiny::downloadHandler(
+        filename = paste0("regression_plot.", input$plot_type),
+        content = function(file) {
+          shiny::withProgress(message = "Saving the plot. Hold on for a moment..", {
+            ggplot2::ggsave(
+              filename = file,
+              plot = rv$plot,
+              width = input$plot_width,
+              height = input$plot_height,
+              dpi = 300,
+              units = "mm", scale = 2
+            )
+          })
+        }
+      )
+
       ##############################################################################
       #########
       #########  Model checks
@@ -477,171 +650,6 @@ regression_server <- function(id,
         alt = "Assumptions testing of the multivariable regression model"
       )
 
-      shiny::observeEvent(
-        list(
-          data_r(),
-          regression_vars()
-        ),
-        {
-          rv$list$regression$tables <- NULL
-        }
-      )
-
-      ### Creating the regression table
-      shiny::observeEvent(
-        input$load,
-        {
-          shiny::req(rv$list$regression$models)
-          ## To avoid plotting old models on fail/error
-          rv$list$regression$tables <- NULL
-
-          # browser()
-          tryCatch(
-            {
-              parameters <- list(
-                p.values = input$add_regression_p == "no"
-              )
-
-              out <- lapply(rv$list$regression$models, \(.x){
-                .x$model
-              }) |>
-                purrr::map(\(.x){
-                  do.call(
-                    regression_table,
-                    append_list(.x, parameters, "x")
-                  )
-                })
-
-              rv$list$regression$models |>
-                purrr::imap(\(.x, .i){
-                  rv$list$regression$models[[.i]][["code_table"]] <- paste(
-                    .x$code,
-                    expression_string(rlang::call2(.fn = "regression_table", !!!parameters, .ns = "FreesearchR"), assign.str = NULL),
-                    sep = "|>\n"
-                  )
-                })
-
-              rv$list$regression$tables <- out
-              rv$list$input <- input
-            },
-            warning = function(warn) {
-              showNotification(paste0(warn), type = "warning")
-            },
-            error = function(err) {
-              showNotification(paste0("Creating a regression table failed with the following error: ", err), type = "err")
-            }
-          )
-        }
-      )
-
-      ## Consider creating merged table with theming and then passing object
-      ## to render.
-
-      output$table2 <- gt::render_gt({
-        ## Print checks if a regression table is present
-        if (!is.null(rv$list$regression$tables)) {
-          gtsummary::theme_gtsummary_journal(journal = "jama")
-          merged <- rv$list$regression$tables |>
-            tbl_merge()
-
-          if (input$add_regression_p == "no") {
-            merged <- merged |>
-              gtsummary::modify_column_hide(column = dplyr::starts_with("p.value"))
-          }
-
-          out <- merged |>
-            gtsummary::as_gt() |>
-            gt::tab_header(gt::md(glue::glue("**Table 2: {rv$list$regression$params$descr}**")))
-
-          rv$list$regression$table_merged
-
-          out
-        } else {
-          return(NULL)
-        }
-      })
-
-      ##############################################################################
-      #########
-      #########  Coefficients plot
-      #########
-      ##############################################################################
-
-      shiny::observeEvent(list(
-        input$plot_model,
-        rv$list$regression
-      ), {
-        shiny::req(input$plot_model)
-
-        tryCatch(
-          {
-            p <- merge_long(
-              rv$list$regression,
-              sort_by(
-                input$plot_model,
-                c("Univariable", "Minimal", "Multivariable"),
-                na.rm = TRUE
-              )
-            ) |>
-              (\(.x){
-                if (length(input$plot_model) > 1) {
-                  plot.tbl_regression(
-                    x = .x,
-                    colour = "model",
-                    dodged = TRUE
-                  ) +
-                    ggplot2::theme(legend.position = "bottom") +
-                    ggplot2::guides(color = ggplot2::guide_legend(reverse = TRUE))
-                } else {
-                  plot.tbl_regression(
-                    x = .x,
-                    colour = "variable"
-                  ) +
-                    ggplot2::theme(legend.position = "none")
-                }
-              })()
-
-            rv$plot <- p +
-              ggplot2::scale_y_discrete(labels = scales::label_wrap(15)) +
-              gg_theme_shiny()
-          },
-          error = function(err) {
-            showNotification(paste0(err), type = "err")
-          }
-        )
-      })
-
-
-      output$regression_plot <- shiny::renderPlot(
-        {
-          shiny::req(input$plot_model)
-
-          rv$plot
-        },
-        alt = "Regression coefficient plot"
-      )
-
-      # plot_download_server(
-      #   id = ns("reg_plot_download"),
-      #   data = shiny::reactive(rv$plot)
-      # )
-
-      output$download_plot <- shiny::downloadHandler(
-        filename = paste0("regression_plot.", input$plot_type),
-        content = function(file) {
-          shiny::withProgress(message = "Saving the plot. Hold on for a moment..", {
-            ggplot2::ggsave(
-              filename = file,
-              plot = rv$plot,
-              width = input$plot_width,
-              height = input$plot_height,
-              dpi = 300,
-              units = "mm", scale = 2
-            )
-          })
-        }
-      )
-
       ##############################################################################
       #########
       #########  Output

R/regression_table.R

@@ -140,7 +140,7 @@ regression_table_create <- function(x, ..., args.list = NULL, fun = "gtsummary::
     }
   }
 
-  # gtsummary::theme_gtsummary_journal(journal = theme)
+  gtsummary::theme_gtsummary_journal(journal = theme)
   if (inherits(x, "polr")) {
     # browser()
     out <- do.call(getfun(fun), c(list(x = x), args.list))

SESSION.md

@@ -11,64 +11,89 @@
 |collate     |en_US.UTF-8                                |
 |ctype       |en_US.UTF-8                                |
 |tz          |Europe/Copenhagen                          |
-|date        |2025-05-10                                 |
+|date        |2025-05-14                                 |
 |rstudio     |2024.12.1+563 Kousa Dogwood (desktop)      |
 |pandoc      |3.6.4 @ /opt/homebrew/bin/ (via rmarkdown) |
 |quarto      |1.7.30 @ /usr/local/bin/quarto             |
-|FreesearchR |25.5.4.250510                              |
+|FreesearchR |25.5.5.250514                              |
                                                                                 
                                                                                 
 --------------------------------------------------------------------------------
 ----------------------------------- packages -----------------------------------
 --------------------------------------------------------------------------------
 |package           |loadedversion |date       |source         |
-|:-------------|:-------------|:----------|:--------------|
+|:-----------------|:-------------|:----------|:--------------|
 |apexcharter       |0.4.4         |2024-09-06 |CRAN (R 4.4.1) |
 |askpass           |1.2.1         |2024-10-04 |CRAN (R 4.4.1) |
 |assertthat        |0.2.1         |2019-03-21 |CRAN (R 4.4.1) |
 |backports         |1.5.0         |2024-05-23 |CRAN (R 4.4.1) |
+|base64enc         |0.1-3         |2015-07-28 |CRAN (R 4.4.1) |
 |bayestestR        |0.15.3        |2025-04-28 |CRAN (R 4.4.1) |
 |bit               |4.6.0         |2025-03-06 |CRAN (R 4.4.1) |
 |bit64             |4.6.0-1       |2025-01-16 |CRAN (R 4.4.1) |
+|bitops            |1.0-9         |2024-10-03 |CRAN (R 4.4.1) |
 |boot              |1.3-31        |2024-08-28 |CRAN (R 4.4.1) |
+|brio              |1.1.5         |2024-04-24 |CRAN (R 4.4.1) |
 |broom             |1.0.8         |2025-03-28 |CRAN (R 4.4.1) |
 |broom.helpers     |1.21.0        |2025-04-24 |CRAN (R 4.4.1) |
 |bsicons           |0.1.2         |2023-11-04 |CRAN (R 4.4.0) |
 |bslib             |0.9.0         |2025-01-30 |CRAN (R 4.4.1) |
 |cachem            |1.1.0         |2024-05-16 |CRAN (R 4.4.1) |
+|cards             |0.6.0         |2025-04-11 |CRAN (R 4.4.1) |
+|cardx             |0.2.4         |2025-04-12 |CRAN (R 4.4.1) |
+|caTools           |1.18.3        |2024-09-04 |CRAN (R 4.4.1) |
 |cellranger        |1.1.0         |2016-07-27 |CRAN (R 4.4.0) |
 |cffr              |1.2.0         |2025-01-25 |CRAN (R 4.4.1) |
+|checkmate         |2.3.2         |2024-07-29 |CRAN (R 4.4.0) |
 |class             |7.3-23        |2025-01-01 |CRAN (R 4.4.1) |
 |classInt          |0.4-11        |2025-01-08 |CRAN (R 4.4.1) |
 |cli               |3.6.5         |2025-04-23 |CRAN (R 4.4.1) |
+|cluster           |2.1.8.1       |2025-03-12 |CRAN (R 4.4.1) |
+|codetools         |0.2-20        |2024-03-31 |CRAN (R 4.4.1) |
+|colorspace        |2.1-1         |2024-07-26 |CRAN (R 4.4.1) |
 |commonmark        |1.9.5         |2025-03-17 |CRAN (R 4.4.1) |
-|correlation   |0.8.7         |2025-03-03 |CRAN (R 4.4.1) |
 |crayon            |1.5.3         |2024-06-20 |CRAN (R 4.4.1) |
 |curl              |6.2.2         |2025-03-24 |CRAN (R 4.4.1) |
 |data.table        |1.17.0        |2025-02-22 |CRAN (R 4.4.1) |
 |datamods          |1.5.3         |2024-10-02 |CRAN (R 4.4.1) |
 |datawizard        |1.0.2         |2025-03-24 |CRAN (R 4.4.1) |
+|DEoptimR          |1.1-3-1       |2024-11-23 |CRAN (R 4.4.1) |
 |desc              |1.4.3         |2023-12-10 |CRAN (R 4.4.1) |
 |devtools          |2.4.5         |2022-10-11 |CRAN (R 4.4.0) |
 |DHARMa            |0.4.7         |2024-10-18 |CRAN (R 4.4.1) |
 |digest            |0.6.37        |2024-08-19 |CRAN (R 4.4.1) |
+|doParallel        |1.0.17        |2022-02-07 |CRAN (R 4.4.0) |
 |dplyr             |1.1.4         |2023-11-17 |CRAN (R 4.4.0) |
 |DT                |0.33          |2024-04-04 |CRAN (R 4.4.0) |
 |e1071             |1.7-16        |2024-09-16 |CRAN (R 4.4.1) |
 |easystats         |0.7.4         |2025-02-06 |CRAN (R 4.4.1) |
-|effectsize    |1.0.0         |2024-12-10 |CRAN (R 4.4.1) |
 |ellipsis          |0.3.2         |2021-04-29 |CRAN (R 4.4.1) |
+|emmeans           |1.11.1        |2025-05-04 |CRAN (R 4.4.1) |
+|esquisse          |2.1.0         |2025-02-21 |CRAN (R 4.4.1) |
+|estimability      |1.5.1         |2024-05-12 |CRAN (R 4.4.0) |
 |eulerr            |7.0.2         |2024-03-28 |CRAN (R 4.4.0) |
 |evaluate          |1.0.3         |2025-01-10 |CRAN (R 4.4.1) |
 |farver            |2.1.2         |2024-05-13 |CRAN (R 4.4.1) |
 |fastmap           |1.2.0         |2024-05-15 |CRAN (R 4.4.1) |
+|flextable         |0.9.7         |2024-10-27 |CRAN (R 4.4.1) |
 |fontawesome       |0.5.3         |2024-11-16 |CRAN (R 4.4.1) |
+|fontBitstreamVera |0.1.1         |2017-02-01 |CRAN (R 4.4.1) |
+|fontLiberation    |0.1.0         |2016-10-15 |CRAN (R 4.4.1) |
+|fontquiver        |0.2.1         |2017-02-01 |CRAN (R 4.4.0) |
 |forcats           |1.0.0         |2023-01-29 |CRAN (R 4.4.0) |
+|foreach           |1.5.2         |2022-02-02 |CRAN (R 4.4.0) |
+|foreign           |0.8-90        |2025-03-31 |CRAN (R 4.4.1) |
+|Formula           |1.2-5         |2023-02-24 |CRAN (R 4.4.1) |
+|FreesearchR       |25.5.5        |NA         |NA             |
 |fs                |1.6.6         |2025-04-12 |CRAN (R 4.4.1) |
+|gdtools           |0.4.2         |2025-03-27 |CRAN (R 4.4.1) |
 |generics          |0.1.3         |2022-07-05 |CRAN (R 4.4.1) |
 |ggalluvial        |0.12.5        |2023-02-22 |CRAN (R 4.4.0) |
+|ggcorrplot        |0.1.4.1       |2023-09-05 |CRAN (R 4.4.0) |
 |ggforce           |0.4.2         |2024-02-19 |CRAN (R 4.4.0) |
 |ggplot2           |3.5.2         |2025-04-09 |CRAN (R 4.4.1) |
+|ggridges          |0.5.6         |2024-01-23 |CRAN (R 4.4.0) |
+|ggstats           |0.9.0         |2025-03-10 |CRAN (R 4.4.1) |
 |glue              |1.8.0         |2024-09-30 |CRAN (R 4.4.1) |
 |gridExtra         |2.3           |2017-09-09 |CRAN (R 4.4.1) |
 |gt                |1.0.0         |2025-04-05 |CRAN (R 4.4.1) |
@@ -76,23 +101,26 @@
 |gtsummary         |2.2.0         |2025-04-14 |CRAN (R 4.4.1) |
 |haven             |2.5.4         |2023-11-30 |CRAN (R 4.4.0) |
 |here              |1.0.1         |2020-12-13 |CRAN (R 4.4.1) |
+|Hmisc             |5.2-3         |2025-03-16 |CRAN (R 4.4.1) |
 |hms               |1.1.3         |2023-03-21 |CRAN (R 4.4.0) |
+|htmlTable         |2.4.3         |2024-07-21 |CRAN (R 4.4.0) |
 |htmltools         |0.5.8.1       |2024-04-04 |CRAN (R 4.4.1) |
 |htmlwidgets       |1.6.4         |2023-12-06 |CRAN (R 4.4.0) |
 |httpuv            |1.6.16        |2025-04-16 |CRAN (R 4.4.1) |
 |IDEAFilter        |0.2.0         |2024-04-15 |CRAN (R 4.4.0) |
 |insight           |1.2.0         |2025-04-22 |CRAN (R 4.4.1) |
+|iterators         |1.0.14        |2022-02-05 |CRAN (R 4.4.1) |
 |jquerylib         |0.1.4         |2021-04-26 |CRAN (R 4.4.0) |
 |jsonlite          |2.0.0         |2025-03-27 |CRAN (R 4.4.1) |
 |jsonvalidate      |1.5.0         |2025-02-07 |CRAN (R 4.4.1) |
 |KernSmooth        |2.23-26       |2025-01-01 |CRAN (R 4.4.1) |
 |keyring           |1.3.2         |2023-12-11 |CRAN (R 4.4.0) |
 |knitr             |1.50          |2025-03-16 |CRAN (R 4.4.1) |
-|labeling      |0.4.3         |2023-08-29 |CRAN (R 4.4.1) |
 |later             |1.4.2         |2025-04-08 |CRAN (R 4.4.1) |
 |lattice           |0.22-7        |2025-04-02 |CRAN (R 4.4.1) |
 |lifecycle         |1.0.4         |2023-11-07 |CRAN (R 4.4.1) |
 |lme4              |1.1-37        |2025-03-26 |CRAN (R 4.4.1) |
+|lubridate         |1.9.4         |2024-12-08 |CRAN (R 4.4.1) |
 |magrittr          |2.0.3         |2022-03-30 |CRAN (R 4.4.1) |
 |MASS              |7.3-65        |2025-02-28 |CRAN (R 4.4.1) |
 |Matrix            |1.7-3         |2025-03-11 |CRAN (R 4.4.1) |
@@ -100,38 +128,42 @@
 |mime              |0.13          |2025-03-17 |CRAN (R 4.4.1) |
 |miniUI            |0.1.2         |2025-04-17 |CRAN (R 4.4.1) |
 |minqa             |1.2.8         |2024-08-17 |CRAN (R 4.4.1) |
-|modelbased    |0.10.0        |2025-03-10 |CRAN (R 4.4.1) |
+|mvtnorm           |1.3-3         |2025-01-10 |CRAN (R 4.4.1) |
 |nlme              |3.1-168       |2025-03-31 |CRAN (R 4.4.1) |
 |nloptr            |2.2.1         |2025-03-17 |CRAN (R 4.4.1) |
+|nnet              |7.3-20        |2025-01-01 |CRAN (R 4.4.1) |
+|officer           |0.6.8         |2025-03-23 |CRAN (R 4.4.1) |
+|opdisDownsampling |1.0.1         |2024-04-15 |CRAN (R 4.4.0) |
 |openssl           |2.3.2         |2025-02-03 |CRAN (R 4.4.1) |
 |openxlsx2         |1.15          |2025-04-25 |CRAN (R 4.4.1) |
 |parameters        |0.24.2        |2025-03-04 |CRAN (R 4.4.1) |
 |patchwork         |1.3.0         |2024-09-16 |CRAN (R 4.4.1) |
+|pbmcapply         |1.5.1         |2022-04-28 |CRAN (R 4.4.1) |
 |performance       |0.13.0        |2025-01-15 |CRAN (R 4.4.1) |
 |phosphoricons     |0.2.1         |2024-04-08 |CRAN (R 4.4.0) |
 |pillar            |1.10.2        |2025-04-05 |CRAN (R 4.4.1) |
 |pkgbuild          |1.4.7         |2025-03-24 |CRAN (R 4.4.1) |
 |pkgconfig         |2.0.3         |2019-09-22 |CRAN (R 4.4.1) |
 |pkgload           |1.4.0         |2024-06-28 |CRAN (R 4.4.0) |
+|plyr              |1.8.9         |2023-10-02 |CRAN (R 4.4.1) |
 |polyclip          |1.10-7        |2024-07-23 |CRAN (R 4.4.1) |
-|polylabelr    |0.3.0         |2024-11-19 |CRAN (R 4.4.1) |
+|pracma            |2.4.4         |2023-11-10 |CRAN (R 4.4.1) |
 |processx          |3.8.6         |2025-02-21 |CRAN (R 4.4.1) |
 |profvis           |0.4.0         |2024-09-20 |CRAN (R 4.4.1) |
 |promises          |1.3.2         |2024-11-28 |CRAN (R 4.4.1) |
 |proxy             |0.4-27        |2022-06-09 |CRAN (R 4.4.1) |
 |ps                |1.9.1         |2025-04-12 |CRAN (R 4.4.1) |
 |purrr             |1.0.4         |2025-02-05 |CRAN (R 4.4.1) |
+|qqconf            |1.3.2         |2023-04-14 |CRAN (R 4.4.0) |
+|qqplotr           |0.0.6         |2023-01-25 |CRAN (R 4.4.0) |
 |quarto            |1.4.4         |2024-07-20 |CRAN (R 4.4.0) |
-|R.cache       |0.16.0        |2022-07-21 |CRAN (R 4.4.0) |
-|R.methodsS3   |1.8.2         |2022-06-13 |CRAN (R 4.4.1) |
-|R.oo          |1.27.0        |2024-11-01 |CRAN (R 4.4.1) |
-|R.utils       |2.13.0        |2025-02-24 |CRAN (R 4.4.1) |
 |R6                |2.6.1         |2025-02-15 |CRAN (R 4.4.1) |
 |ragg              |1.4.0         |2025-04-10 |CRAN (R 4.4.1) |
 |rankinPlot        |1.1.0         |2023-01-30 |CRAN (R 4.4.0) |
 |rbibutils         |2.3           |2024-10-04 |CRAN (R 4.4.1) |
 |RColorBrewer      |1.1-3         |2022-04-03 |CRAN (R 4.4.1) |
 |Rcpp              |1.0.14        |2025-01-12 |CRAN (R 4.4.1) |
+|RcppArmadillo     |14.4.2-1      |2025-04-25 |CRAN (R 4.4.1) |
 |Rdpack            |2.6.4         |2025-04-09 |CRAN (R 4.4.1) |
 |reactable         |0.4.4         |2023-03-12 |CRAN (R 4.4.0) |
 |readODS           |2.3.2         |2025-01-13 |CRAN (R 4.4.1) |
@@ -141,12 +173,15 @@
 |REDCapR           |1.4.0         |2025-01-11 |CRAN (R 4.4.1) |
 |reformulas        |0.4.0         |2024-11-03 |CRAN (R 4.4.1) |
 |remotes           |2.5.0         |2024-03-17 |CRAN (R 4.4.1) |
+|rempsyc           |0.1.9         |2025-02-01 |CRAN (R 4.4.1) |
 |renv              |1.1.4         |2025-03-20 |CRAN (R 4.4.1) |
-|report        |0.6.1         |2025-02-07 |CRAN (R 4.4.1) |
+|reshape2          |1.4.4         |2020-04-09 |CRAN (R 4.4.0) |
 |rio               |1.2.3         |2024-09-25 |CRAN (R 4.4.1) |
 |rlang             |1.1.6         |2025-04-11 |CRAN (R 4.4.1) |
 |rmarkdown         |2.29          |2024-11-04 |CRAN (R 4.4.1) |
+|robustbase        |0.99-4-1      |2024-09-27 |CRAN (R 4.4.1) |
 |roxygen2          |7.3.2         |2024-06-28 |CRAN (R 4.4.0) |
+|rpart             |4.1.24        |2025-01-07 |CRAN (R 4.4.1) |
 |rprojroot         |2.0.4         |2023-11-05 |CRAN (R 4.4.1) |
 |rsconnect         |1.3.4         |2025-01-22 |CRAN (R 4.4.1) |
 |rstudioapi        |0.17.1        |2024-10-22 |CRAN (R 4.4.1) |
@@ -161,22 +196,23 @@
 |shinyWidgets      |0.9.0         |2025-02-21 |CRAN (R 4.4.1) |
 |stringi           |1.8.7         |2025-03-27 |CRAN (R 4.4.1) |
 |stringr           |1.5.1         |2023-11-14 |CRAN (R 4.4.0) |
-|styler        |1.10.3        |2024-04-07 |CRAN (R 4.4.0) |
 |systemfonts       |1.2.2         |2025-04-04 |CRAN (R 4.4.1) |
+|testthat          |3.2.3         |2025-01-13 |CRAN (R 4.4.1) |
 |textshaping       |1.0.0         |2025-01-20 |CRAN (R 4.4.1) |
+|thematic          |0.1.6         |2024-07-29 |CRAN (R 4.4.0) |
 |tibble            |3.2.1         |2023-03-20 |CRAN (R 4.4.0) |
 |tidyr             |1.3.1         |2024-01-24 |CRAN (R 4.4.1) |
 |tidyselect        |1.2.1         |2024-03-11 |CRAN (R 4.4.0) |
+|timechange        |0.3.0         |2024-01-18 |CRAN (R 4.4.1) |
 |toastui           |0.4.0         |2025-04-03 |CRAN (R 4.4.1) |
 |tweenr            |2.0.3         |2024-02-26 |CRAN (R 4.4.0) |
+|twosamples        |2.0.1         |2023-06-23 |CRAN (R 4.4.1) |
 |tzdb              |0.5.0         |2025-03-15 |CRAN (R 4.4.1) |
 |urlchecker        |1.0.1         |2021-11-30 |CRAN (R 4.4.1) |
 |usethis           |3.1.0         |2024-11-26 |CRAN (R 4.4.1) |
-|utf8          |1.2.4         |2023-10-22 |CRAN (R 4.4.1) |
+|uuid              |1.2-1         |2024-07-29 |CRAN (R 4.4.1) |
 |V8                |6.0.3         |2025-03-26 |CRAN (R 4.4.1) |
 |vctrs             |0.6.5         |2023-12-01 |CRAN (R 4.4.0) |
-|viridis       |0.6.5         |2024-01-29 |CRAN (R 4.4.0) |
-|viridisLite   |0.4.2         |2023-05-02 |CRAN (R 4.4.1) |
 |vroom             |1.6.5         |2023-12-05 |CRAN (R 4.4.0) |
 |withr             |3.0.2         |2024-10-28 |CRAN (R 4.4.1) |
 |writexl           |1.5.4         |2025-04-15 |CRAN (R 4.4.1) |

inst/apps/FreesearchR/app.R

@@ -49,7 +49,7 @@ library(rlang)
 #### Current file: /Users/au301842/FreesearchR/R//app_version.R 
 ########
 
-app_version <- function()'25.5.4'
+app_version <- function()'25.5.5'
 
 
 ########
@@ -3996,7 +3996,7 @@ simple_snake <- function(data){
 #### Current file: /Users/au301842/FreesearchR/R//hosted_version.R 
 ########
 
-hosted_version <- function()'v25.5.4-250513'
+hosted_version <- function()'v25.5.5-250514'
 
 
 ########
@@ -7134,7 +7134,7 @@ regression_table_create <- function(x, ..., args.list = NULL, fun = "gtsummary::
     }
   }
 
-  # gtsummary::theme_gtsummary_journal(journal = theme)
+  gtsummary::theme_gtsummary_journal(journal = theme)
   if (inherits(x, "polr")) {
     # browser()
     out <- do.call(getfun(fun), c(list(x = x), args.list))
@@ -7505,7 +7505,7 @@ regression_server <- function(id,
 
       ##############################################################################
       #########
-      #########  Regression analysis
+      #########  Regression models
       #########
       ##############################################################################
 
@@ -7553,6 +7553,179 @@ regression_server <- function(id,
         }
       )
 
+
+
+      shiny::observeEvent(
+        list(
+          data_r(),
+          regression_vars()
+        ),
+        {
+          rv$list$regression$tables <- NULL
+        }
+      )
+
+      ##############################################################################
+      #########
+      #########  Regression table
+      #########
+      ##############################################################################
+
+      ### Creating the regression table
+      shiny::observeEvent(
+        input$load,
+        {
+          shiny::req(rv$list$regression$models)
+          ## To avoid plotting old models on fail/error
+          rv$list$regression$tables <- NULL
+
+          # browser()
+          tryCatch(
+            {
+              parameters <- list(
+                p.values = input$add_regression_p == "no"
+              )
+
+              out <- lapply(rv$list$regression$models, \(.x){
+                .x$model
+              }) |>
+                purrr::map(\(.x){
+                  do.call(
+                    regression_table,
+                    append_list(.x, parameters, "x")
+                  )
+                })
+
+              rv$list$regression$models |>
+                purrr::imap(\(.x, .i){
+                  rv$list$regression$models[[.i]][["code_table"]] <- paste(
+                    .x$code,
+                    expression_string(rlang::call2(.fn = "regression_table", !!!parameters, .ns = "FreesearchR"), assign.str = NULL),
+                    sep = "|>\n"
+                  )
+                })
+
+              rv$list$regression$tables <- out
+              rv$list$input <- input
+            },
+            warning = function(warn) {
+              showNotification(paste0(warn), type = "warning")
+            },
+            error = function(err) {
+              showNotification(paste0("Creating a regression table failed with the following error: ", err), type = "err")
+            }
+          )
+        }
+      )
+
+      ## Consider creating merged table with theming and then passing object
+      ## to render.
+
+      output$table2 <- gt::render_gt({
+        ## Print checks if a regression table is present
+        if (!is.null(rv$list$regression$tables)) {
+          # gtsummary::theme_gtsummary_journal(journal = "jama")
+          merged <- rv$list$regression$tables |>
+            tbl_merge()
+
+          if (input$add_regression_p == "no") {
+            merged <- merged |>
+              gtsummary::modify_column_hide(column = dplyr::starts_with("p.value"))
+          }
+
+          out <- merged |>
+            gtsummary::as_gt() |>
+            gt::tab_header(gt::md(glue::glue("**Table 2: {rv$list$regression$params$descr}**")))
+
+          # rv$list$regression$table_merged <- out
+
+          out
+        } else {
+          return(NULL)
+        }
+      })
+
+      ##############################################################################
+      #########
+      #########  Coefficients plot
+      #########
+      ##############################################################################
+
+      shiny::observeEvent(list(
+        input$plot_model,
+        rv$list$regression
+      ), {
+        shiny::req(input$plot_model)
+
+        tryCatch(
+          {
+            p <- merge_long(
+              rv$list$regression,
+              sort_by(
+                input$plot_model,
+                c("Univariable", "Minimal", "Multivariable"),
+                na.rm = TRUE
+              )
+            ) |>
+              (\(.x){
+                if (length(input$plot_model) > 1) {
+                  plot.tbl_regression(
+                    x = .x,
+                    colour = "model",
+                    dodged = TRUE
+                  ) +
+                    ggplot2::theme(legend.position = "bottom") +
+                    ggplot2::guides(color = ggplot2::guide_legend(reverse = TRUE))
+                } else {
+                  plot.tbl_regression(
+                    x = .x,
+                    colour = "variable"
+                  ) +
+                    ggplot2::theme(legend.position = "none")
+                }
+              })()
+
+            rv$plot <- p +
+              ggplot2::scale_y_discrete(labels = scales::label_wrap(15)) +
+              gg_theme_shiny()
+          },
+          error = function(err) {
+            showNotification(paste0(err), type = "err")
+          }
+        )
+      })
+
+
+      output$regression_plot <- shiny::renderPlot(
+        {
+          shiny::req(input$plot_model)
+
+          rv$plot
+        },
+        alt = "Regression coefficient plot"
+      )
+
+      # plot_download_server(
+      #   id = ns("reg_plot_download"),
+      #   data = shiny::reactive(rv$plot)
+      # )
+
+      output$download_plot <- shiny::downloadHandler(
+        filename = paste0("regression_plot.", input$plot_type),
+        content = function(file) {
+          shiny::withProgress(message = "Saving the plot. Hold on for a moment..", {
+            ggplot2::ggsave(
+              filename = file,
+              plot = rv$plot,
+              width = input$plot_width,
+              height = input$plot_height,
+              dpi = 300,
+              units = "mm", scale = 2
+            )
+          })
+        }
+      )
+
       ##############################################################################
       #########
       #########  Model checks
@@ -7660,171 +7833,6 @@ regression_server <- function(id,
         alt = "Assumptions testing of the multivariable regression model"
       )
 
-      shiny::observeEvent(
-        list(
-          data_r(),
-          regression_vars()
-        ),
-        {
-          rv$list$regression$tables <- NULL
-        }
-      )
-
-      ### Creating the regression table
-      shiny::observeEvent(
-        input$load,
-        {
-          shiny::req(rv$list$regression$models)
-          ## To avoid plotting old models on fail/error
-          rv$list$regression$tables <- NULL
-
-          # browser()
-          tryCatch(
-            {
-              parameters <- list(
-                p.values = input$add_regression_p == "no"
-              )
-
-              out <- lapply(rv$list$regression$models, \(.x){
-                .x$model
-              }) |>
-                purrr::map(\(.x){
-                  do.call(
-                    regression_table,
-                    append_list(.x, parameters, "x")
-                  )
-                })
-
-              rv$list$regression$models |>
-                purrr::imap(\(.x, .i){
-                  rv$list$regression$models[[.i]][["code_table"]] <- paste(
-                    .x$code,
-                    expression_string(rlang::call2(.fn = "regression_table", !!!parameters, .ns = "FreesearchR"), assign.str = NULL),
-                    sep = "|>\n"
-                  )
-                })
-
-              rv$list$regression$tables <- out
-              rv$list$input <- input
-            },
-            warning = function(warn) {
-              showNotification(paste0(warn), type = "warning")
-            },
-            error = function(err) {
-              showNotification(paste0("Creating a regression table failed with the following error: ", err), type = "err")
-            }
-          )
-        }
-      )
-
-      ## Consider creating merged table with theming and then passing object
-      ## to render.
-
-      output$table2 <- gt::render_gt({
-        ## Print checks if a regression table is present
-        if (!is.null(rv$list$regression$tables)) {
-          gtsummary::theme_gtsummary_journal(journal = "jama")
-          merged <- rv$list$regression$tables |>
-            tbl_merge()
-
-          if (input$add_regression_p == "no") {
-            merged <- merged |>
-              gtsummary::modify_column_hide(column = dplyr::starts_with("p.value"))
-          }
-
-          out <- merged |>
-            gtsummary::as_gt() |>
-            gt::tab_header(gt::md(glue::glue("**Table 2: {rv$list$regression$params$descr}**")))
-
-          rv$list$regression$table_merged
-
-          out
-        } else {
-          return(NULL)
-        }
-      })
-
-      ##############################################################################
-      #########
-      #########  Coefficients plot
-      #########
-      ##############################################################################
-
-      shiny::observeEvent(list(
-        input$plot_model,
-        rv$list$regression
-      ), {
-        shiny::req(input$plot_model)
-
-        tryCatch(
-          {
-            p <- merge_long(
-              rv$list$regression,
-              sort_by(
-                input$plot_model,
-                c("Univariable", "Minimal", "Multivariable"),
-                na.rm = TRUE
-              )
-            ) |>
-              (\(.x){
-                if (length(input$plot_model) > 1) {
-                  plot.tbl_regression(
-                    x = .x,
-                    colour = "model",
-                    dodged = TRUE
-                  ) +
-                    ggplot2::theme(legend.position = "bottom") +
-                    ggplot2::guides(color = ggplot2::guide_legend(reverse = TRUE))
-                } else {
-                  plot.tbl_regression(
-                    x = .x,
-                    colour = "variable"
-                  ) +
-                    ggplot2::theme(legend.position = "none")
-                }
-              })()
-
-            rv$plot <- p +
-              ggplot2::scale_y_discrete(labels = scales::label_wrap(15)) +
-              gg_theme_shiny()
-          },
-          error = function(err) {
-            showNotification(paste0(err), type = "err")
-          }
-        )
-      })
-
-
-      output$regression_plot <- shiny::renderPlot(
-        {
-          shiny::req(input$plot_model)
-
-          rv$plot
-        },
-        alt = "Regression coefficient plot"
-      )
-
-      # plot_download_server(
-      #   id = ns("reg_plot_download"),
-      #   data = shiny::reactive(rv$plot)
-      # )
-
-      output$download_plot <- shiny::downloadHandler(
-        filename = paste0("regression_plot.", input$plot_type),
-        content = function(file) {
-          shiny::withProgress(message = "Saving the plot. Hold on for a moment..", {
-            ggplot2::ggsave(
-              filename = file,
-              plot = rv$plot,
-              width = input$plot_width,
-              height = input$plot_height,
-              dpi = 300,
-              units = "mm", scale = 2
-            )
-          })
-        }
-      )
-
       ##############################################################################
       #########
       #########  Output

renv.lock

@@ -2710,6 +2710,86 @@
       "Author": "Mattan S. Ben-Shachar [aut, cre] (<https://orcid.org/0000-0002-4287-4801>), Dominique Makowski [aut] (<https://orcid.org/0000-0001-5375-9967>), Daniel Lüdecke [aut] (<https://orcid.org/0000-0002-8895-3206>), Indrajeet Patil [aut] (<https://orcid.org/0000-0003-1995-6531>), Brenton M. Wiernik [aut] (<https://orcid.org/0000-0001-9560-6336>), Rémi Thériault [aut] (<https://orcid.org/0000-0003-4315-6788>), Ken Kelley [ctb], David Stanley [ctb], Aaron Caldwell [ctb] (<https://orcid.org/0000-0002-4541-6283>), Jessica Burnett [rev] (<https://orcid.org/0000-0002-0896-5099>), Johannes Karreth [rev] (<https://orcid.org/0000-0003-4586-7153>), Philip Waggoner [aut, ctb] (<https://orcid.org/0000-0002-7825-7573>)",
       "Repository": "CRAN"
     },
+    "emmeans": {
+      "Package": "emmeans",
+      "Version": "1.11.1",
+      "Source": "Repository",
+      "Type": "Package",
+      "Title": "Estimated Marginal Means, aka Least-Squares Means",
+      "Date": "2025-05-03",
+      "Authors@R": "c(person(\"Russell V.\", \"Lenth\", role = c(\"aut\", \"cre\", \"cph\"),  email = \"russell-lenth@uiowa.edu\"), person(\"Balazs\", \"Banfai\", role = \"ctb\"), person(\"Ben\", \"Bolker\", role = \"ctb\"), person(\"Paul\", \"Buerkner\", role = \"ctb\"), person(\"Iago\", \"Giné-Vázquez\", role = \"ctb\"), person(\"Maxime\", \"Herve\", role = \"ctb\"), person(\"Maarten\", \"Jung\", role = \"ctb\"), person(\"Jonathon\", \"Love\", role = \"ctb\"), person(\"Fernando\", \"Miguez\", role = \"ctb\"), person(\"Julia\", \"Piaskowski\", role = \"ctb\"), person(\"Hannes\", \"Riebl\", role = \"ctb\"), person(\"Henrik\", \"Singmann\", role = \"ctb\"))",
+      "Depends": [
+        "R (>= 4.1.0)"
+      ],
+      "Imports": [
+        "estimability (>= 1.4.1)",
+        "graphics",
+        "methods",
+        "mvtnorm",
+        "numDeriv",
+        "stats",
+        "utils"
+      ],
+      "Suggests": [
+        "bayesplot",
+        "bayestestR",
+        "biglm",
+        "brms",
+        "car",
+        "coda (>= 0.17)",
+        "compositions",
+        "ggplot2",
+        "knitr",
+        "lattice",
+        "lme4",
+        "lmerTest (>= 2.0.32)",
+        "logspline",
+        "MASS",
+        "mediation",
+        "mgcv",
+        "multcomp",
+        "multcompView",
+        "MuMIn",
+        "nlme",
+        "ordinal (>= 2014.11-12)",
+        "pbkrtest (>= 0.4-1)",
+        "rmarkdown",
+        "rsm",
+        "sandwich",
+        "scales",
+        "splines",
+        "testthat",
+        "tibble",
+        "xtable (>= 1.8-2)"
+      ],
+      "Enhances": [
+        "CARBayes",
+        "coxme",
+        "gee",
+        "geepack",
+        "MCMCglmm",
+        "MCMCpack",
+        "mice",
+        "nnet",
+        "pscl",
+        "rstanarm",
+        "sommer",
+        "survival"
+      ],
+      "URL": "https://rvlenth.github.io/emmeans/,https://rvlenth.github.io/emmeans/",
+      "BugReports": "https://github.com/rvlenth/emmeans/issues",
+      "LazyData": "yes",
+      "ByteCompile": "yes",
+      "Description": "Obtain estimated marginal means (EMMs) for many linear, generalized  linear, and mixed models. Compute contrasts or linear functions of EMMs, trends, and comparisons of slopes. Plots and other displays. Least-squares means are discussed, and the term \"estimated marginal means\" is suggested, in Searle, Speed, and Milliken (1980) Population marginal means  in the linear model: An alternative to least squares means, The American  Statistician 34(4), 216-221 <doi:10.1080/00031305.1980.10483031>.",
+      "License": "GPL-2 | GPL-3",
+      "Encoding": "UTF-8",
+      "RoxygenNote": "7.3.2",
+      "VignetteBuilder": "knitr",
+      "NeedsCompilation": "no",
+      "Author": "Russell V. Lenth [aut, cre, cph], Balazs Banfai [ctb], Ben Bolker [ctb], Paul Buerkner [ctb], Iago Giné-Vázquez [ctb], Maxime Herve [ctb], Maarten Jung [ctb], Jonathon Love [ctb], Fernando Miguez [ctb], Julia Piaskowski [ctb], Hannes Riebl [ctb], Henrik Singmann [ctb]",
+      "Maintainer": "Russell V. Lenth <russell-lenth@uiowa.edu>",
+      "Repository": "CRAN"
+    },
     "esquisse": {
       "Package": "esquisse",
       "Version": "2.1.0",
@@ -2757,6 +2837,33 @@
       "Maintainer": "Victor Perrier <victor.perrier@dreamrs.fr>",
       "Repository": "CRAN"
     },
+    "estimability": {
+      "Package": "estimability",
+      "Version": "1.5.1",
+      "Source": "Repository",
+      "Type": "Package",
+      "Title": "Tools for Assessing Estimability of Linear Predictions",
+      "Date": "2024-05-12",
+      "Authors@R": "c(person(\"Russell\", \"Lenth\", role = c(\"aut\", \"cre\", \"cph\"),  email = \"russell-lenth@uiowa.edu\"))",
+      "Depends": [
+        "stats",
+        "R(>= 4.1.0)"
+      ],
+      "Suggests": [
+        "knitr",
+        "rmarkdown"
+      ],
+      "Description": "Provides tools for determining estimability of linear functions  of regression coefficients, and 'epredict' methods that handle  non-estimable cases correctly. Estimability theory is discussed in many linear-models textbooks including Chapter 3 of Monahan, JF (2008),  \"A Primer on Linear Models\", Chapman and Hall (ISBN 978-1-4200-6201-4).",
+      "URL": "https://github.com/rvlenth/estimability, https://rvlenth.github.io/estimability/",
+      "BugReports": "https://github.com/rvlenth/estimability/issues",
+      "ByteCompile": "yes",
+      "License": "GPL (>= 3)",
+      "VignetteBuilder": "knitr",
+      "NeedsCompilation": "no",
+      "Author": "Russell Lenth [aut, cre, cph]",
+      "Maintainer": "Russell Lenth <russell-lenth@uiowa.edu>",
+      "Repository": "CRAN"
+    },
     "eulerr": {
       "Package": "eulerr",
       "Version": "7.0.2",
@@ -5407,6 +5514,31 @@
       "Author": "Dominique Makowski [aut, cre] (<https://orcid.org/0000-0001-5375-9967>), Daniel Lüdecke [aut] (<https://orcid.org/0000-0002-8895-3206>), Mattan S. Ben-Shachar [aut] (<https://orcid.org/0000-0002-4287-4801>), Indrajeet Patil [aut] (<https://orcid.org/0000-0003-1995-6531>), Rémi Thériault [aut] (<https://orcid.org/0000-0003-4315-6788>)",
       "Repository": "CRAN"
     },
+    "mvtnorm": {
+      "Package": "mvtnorm",
+      "Version": "1.3-3",
+      "Source": "Repository",
+      "Title": "Multivariate Normal and t Distributions",
+      "Date": "2025-01-09",
+      "Authors@R": "c(person(\"Alan\", \"Genz\", role = \"aut\"), person(\"Frank\", \"Bretz\", role = \"aut\"), person(\"Tetsuhisa\", \"Miwa\", role = \"aut\"), person(\"Xuefei\", \"Mi\", role = \"aut\"), person(\"Friedrich\", \"Leisch\", role = \"ctb\"), person(\"Fabian\", \"Scheipl\", role = \"ctb\"), person(\"Bjoern\", \"Bornkamp\", role = \"ctb\", comment = c(ORCID = \"0000-0002-6294-8185\")), person(\"Martin\", \"Maechler\", role = \"ctb\", comment = c(ORCID = \"0000-0002-8685-9910\")), person(\"Torsten\", \"Hothorn\", role = c(\"aut\", \"cre\"), email = \"Torsten.Hothorn@R-project.org\", comment = c(ORCID = \"0000-0001-8301-0471\")))",
+      "Description": "Computes multivariate normal and t probabilities, quantiles, random deviates,  and densities. Log-likelihoods for multivariate Gaussian models and Gaussian copulae  parameterised by Cholesky factors of covariance or precision matrices are implemented  for interval-censored and exact data, or a mix thereof. Score functions for these  log-likelihoods are available. A class representing multiple lower triangular matrices  and corresponding methods are part of this package.",
+      "Imports": [
+        "stats"
+      ],
+      "Depends": [
+        "R(>= 3.5.0)"
+      ],
+      "Suggests": [
+        "qrng",
+        "numDeriv"
+      ],
+      "License": "GPL-2",
+      "URL": "http://mvtnorm.R-forge.R-project.org",
+      "NeedsCompilation": "yes",
+      "Author": "Alan Genz [aut], Frank Bretz [aut], Tetsuhisa Miwa [aut], Xuefei Mi [aut], Friedrich Leisch [ctb], Fabian Scheipl [ctb], Bjoern Bornkamp [ctb] (<https://orcid.org/0000-0002-6294-8185>), Martin Maechler [ctb] (<https://orcid.org/0000-0002-8685-9910>), Torsten Hothorn [aut, cre] (<https://orcid.org/0000-0001-8301-0471>)",
+      "Maintainer": "Torsten Hothorn <Torsten.Hothorn@R-project.org>",
+      "Repository": "CRAN"
+    },
     "nlme": {
       "Package": "nlme",
       "Version": "3.1-168",
@@ -5493,6 +5625,26 @@
       "Maintainer": "Brian Ripley <Brian.Ripley@R-project.org>",
       "Repository": "CRAN"
     },
+    "numDeriv": {
+      "Package": "numDeriv",
+      "Version": "2016.8-1.1",
+      "Source": "Repository",
+      "Title": "Accurate Numerical Derivatives",
+      "Description": "Methods for calculating (usually) accurate numerical first and second order derivatives. Accurate calculations  are done using 'Richardson''s' extrapolation or, when applicable, a complex step derivative is available. A simple difference  method is also provided. Simple difference is (usually) less accurate but is much quicker than 'Richardson''s' extrapolation and provides a  useful cross-check.  Methods are provided for real scalar and vector valued functions.",
+      "Depends": [
+        "R (>= 2.11.1)"
+      ],
+      "LazyLoad": "yes",
+      "ByteCompile": "yes",
+      "License": "GPL-2",
+      "Copyright": "2006-2011, Bank of Canada. 2012-2016, Paul Gilbert",
+      "Author": "Paul Gilbert and Ravi Varadhan",
+      "Maintainer": "Paul Gilbert <pgilbert.ttv9z@ncf.ca>",
+      "URL": "http://optimizer.r-forge.r-project.org/",
+      "NeedsCompilation": "no",
+      "Repository": "RSPM",
+      "Encoding": "UTF-8"
+    },
     "officer": {
       "Package": "officer",
       "Version": "0.6.8",