version 0.1.1

DESCRIPTION

@@ -1,8 +1,8 @@
 Package: robmedExtra
 Type: Package
 Title: Extra Functionality for (Robust) Mediation Analysis
-Version: 0.1.2
-Date: 2024-11-02
+Version: 0.1.1
+Date: 2024-11-03
 Depends:
     robmed (>= 0.10.0)
 Imports:

NEWS

@@ -0,0 +1,7 @@
+Changes in robmed version 0.1.1
+
+    + Added note in GUI that the resolution of the preview doesn't reflect the selected resolution for the png file.
+
+    + Default in tables is now to include p values of the indirect effects.
+
+    + Updated examples in help files.

R/export_docx.R

@@ -47,19 +47,18 @@
 #' @examples
 #' data("BSG2014")
 #'
-#' # seed to be used for the random number generator
-#' seed <- 20211117
-#'
 #' # perform mediation analysis via robust bootstrap test ROBMED
-#' set.seed(seed)
-#' robust_boot <- test_mediation(BSG2014,
-#'                               x = "ValueDiversity",
-#'                               y = "TeamCommitment",
-#'                               m = "TaskConflict",
-#'                               robust = TRUE)
+#' set.seed(20241101)
+#' boot <- test_mediation(BSG2014,
+#'                        x = "SharedLeadership",
+#'                        y = "TeamPerformance",
+#'                        m = c("ProceduralJustice",
+#'                              "InteractionalJustice"),
+#'                        covariates = c("AgeDiversity",
+#'                                       "GenderDiversity"))
 #'
 #' # construct flextable of results
-#' ft <- to_flextable(robust_boot)
+#' ft <- to_flextable(boot)
 #'
 #' # export to Microsoft Word
 #' file_name <- tempfile(fileext = ".docx")

R/export_pptx.R

@@ -41,19 +41,18 @@
 #' @examples
 #' data("BSG2014")
 #'
-#' # seed to be used for the random number generator
-#' seed <- 20211117
-#'
 #' # perform mediation analysis via robust bootstrap test ROBMED
-#' set.seed(seed)
-#' robust_boot <- test_mediation(BSG2014,
-#'                               x = "ValueDiversity",
-#'                               y = "TeamCommitment",
-#'                               m = "TaskConflict",
-#'                               robust = TRUE)
+#' set.seed(20241101)
+#' boot <- test_mediation(BSG2014,
+#'                        x = "SharedLeadership",
+#'                        y = "TeamPerformance",
+#'                        m = c("ProceduralJustice",
+#'                              "InteractionalJustice"),
+#'                        covariates = c("AgeDiversity",
+#'                                       "GenderDiversity"))
 #'
 #' # construct flextable of results
-#' ft <- to_flextable(robust_boot)
+#' ft <- to_flextable(boot)
 #'
 #' # export to Microsoft Powerpoint
 #' file_name <- tempfile(fileext = ".pptx")

R/to_flextable.R

@@ -68,7 +68,7 @@
 #' data("BSG2014")
 #'
 #' # seed to be used for the random number generator
-#' seed <- 20211117
+#' seed <- 20150601
 #'
 #' # perform mediation analysis via robust bootstrap test ROBMED
 #' set.seed(seed)
@@ -78,6 +78,10 @@
 #'                               m = "TaskConflict",
 #'                               robust = TRUE)
 #'
+#' # note that depending on the seed of the random number
+#' # generator, the p value of the indirect effect may fall
+#' # below or above the arbitrary 5% threshold
+#'
 #' # construct flextable of results
 #' to_flextable(robust_boot)
 #'
@@ -133,13 +137,13 @@ to_flextable.test_mediation <- function(object, type = c("boot", "data"), ...) {
 #' @name to_flextable
 #'
 #' @param p_value  a logical indicating whether to include p-values for the
-#' indirect effects if mediation analysis was done via a bootstrap procedure
-#' (defaults to \code{FALSE}).  If \code{TRUE}, the p-values are obtained via
+#' indirect effects if mediation analysis was done via a bootstrap procedure.
+#' If \code{TRUE} (the default), the p-values are obtained via
 #' \code{\link[robmed]{p_value}()}.
 #'
 #' @export
 
-to_flextable.summary_test_mediation <- function(object, p_value = FALSE, ...) {
+to_flextable.summary_test_mediation <- function(object, p_value = TRUE, ...) {
   # call workhorse function to format tables for effects
   tables <- get_mediation_tables(object, p_value = p_value, ...)
   # put data frames of effects together
@@ -163,7 +167,7 @@ to_flextable.summary_test_mediation <- function(object, p_value = FALSE, ...) {
 #'
 #' @export
 
-to_flextable.list <- function(object, type = c("boot", "data"), p_value = FALSE,
+to_flextable.list <- function(object, type = c("boot", "data"), p_value = TRUE,
                               orientation = c("landscape", "portrait"), ...) {
 
   # check arguments
@@ -293,22 +297,21 @@ to_flextable.list <- function(object, type = c("boot", "data"), p_value = FALSE,
 #' @examples
 #' data("BSG2014")
 #'
-#' # seed to be used for the random number generator
-#' seed <- 20211117
-#'
 #' # perform mediation analysis via robust bootstrap test ROBMED
-#' set.seed(seed)
-#' robust_boot <- test_mediation(BSG2014,
-#'                               x = "ValueDiversity",
-#'                               y = "TeamCommitment",
-#'                               m = "TaskConflict",
-#'                               robust = TRUE)
+#' set.seed(20150601)
+#' boot <- test_mediation(BSG2014,
+#'                        x = "ValueDiversity",
+#'                        y = "TeamCommitment",
+#'                        m = "TaskConflict")
 #'
 #' # construct flextable of results
-#' ft <- to_flextable(robust_boot)
+#' ft <- to_flextable(boot)
 #' # add additional row to the footer
-#' footer_line <- paste("Additional explanations on the conducted",
-#'                      "analysis.")
+#' footer_line <- flextable::as_paragraph(
+#'   "Depending on the seed of the random number generator, the ",
+#'   flextable::as_i("p"), " value of the indirect effect may ",
+#'   "fall below or above the arbitrary 5% threshold."
+#' )
 #' ft <- flextable::add_footer_lines(ft, values = footer_line)
 #' ft <- theme_mediation(ft)
 #' ft

R/to_latex.R

@@ -87,7 +87,7 @@
 #' data("BSG2014")
 #'
 #' # seed to be used for the random number generator
-#' seed <- 20211117
+#' seed <- 20150601
 #'
 #' # perform mediation analysis via robust bootstrap test ROBMED
 #' set.seed(seed)
@@ -97,6 +97,10 @@
 #'                               m = "TaskConflict",
 #'                               robust = TRUE)
 #'
+#' # note that depending on the seed of the random number
+#' # generator, the p value of the indirect effect may fall
+#' # below or above the arbitrary 5% threshold
+#'
 #' # construct LaTeX table of results
 #' to_latex(robust_boot)
 #'
@@ -152,8 +156,8 @@ to_latex.test_mediation <- function(object, type = c("boot", "data"), ...) {
 #' @name to_latex
 #'
 #' @param p_value  a logical indicating whether to include p-values for the
-#' indirect effects if mediation analysis was done via a bootstrap procedure
-#' (defaults to \code{FALSE}).  If \code{TRUE}, the p-values are obtained via
+#' indirect effects if mediation analysis was done via a bootstrap procedure.
+#' If \code{TRUE} (the default), the p-values are obtained via
 #' \code{\link[robmed]{p_value}()}.
 #' @param align  a character vector of length two.  The first element is used
 #' as the alignment specification in the \code{\\begin\{tabular\}\{\}}
@@ -167,7 +171,7 @@ to_latex.test_mediation <- function(object, type = c("boot", "data"), ...) {
 #'
 #' @export
 
-to_latex.summary_test_mediation <- function(object, p_value = FALSE,
+to_latex.summary_test_mediation <- function(object, p_value = TRUE,
                                             align = c("lrrrr", "c"),
                                             ...) {
   # TODO: add checks for argument 'align'
@@ -194,7 +198,7 @@ to_latex.summary_test_mediation <- function(object, p_value = FALSE,
 #'
 #' @export
 
-to_latex.list <- function(object, type = c("boot", "data"), p_value = FALSE,
+to_latex.list <- function(object, type = c("boot", "data"), p_value = TRUE,
                           orientation = c("landscape", "portrait"),
                           align = NULL, ...) {
   # check argument for orientation

README.md

@@ -14,7 +14,7 @@ To cite packages `robmed` and `robmedExtra` in publications, please use:
 
 Alfons, A., Ates, N.Y., & Groenen, P.J.F. (2022b). Robust Mediation Analysis: The `R` Package `robmed`. *Journal of Statistical Software*, **103**(13), 1--45. doi: [10.18637/jss.v103.i13](https://doi.org/10.18637/jss.v103.i13).
 
-Alfons A., Archimbaud A., & Drenth V. (2023). *`robmedExtra`: Extra Functionality for (Robust) Mediation Analysis*. `R` package, <https://CRAN.R-project.org/package=robmedExtra>.
+Alfons A., & Archimbaud A. (2024). *`robmedExtra`: Extra Functionality for (Robust) Mediation Analysis*. `R` package, <https://CRAN.R-project.org/package=robmedExtra>.
 
 ## About ROBMED