release 2.6.2 on CRAN

Author: strengejacke

DESCRIPTION

@@ -2,8 +2,8 @@ Package: sjPlot
 Type: Package
 Encoding: UTF-8
 Title: Data Visualization for Statistics in Social Science
-Version: 2.6.1.9000
-Date: 2018-10-14
+Version: 2.6.2
+Date: 2018-12-18
 Authors@R: c(
     person("Daniel", "Lüdecke", email = "d.luedecke@uke.de", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-8895-3206")),
     person("Carsten", "Schwemmer", email = "carsten.schwemmer@uni-bamberg.de", role = "ctb")
@@ -46,7 +46,6 @@ Imports:
     sjstats (>= 0.17.2),
     tidyr (>= 0.7.0)
 Suggests:
-    AICcmodavg,
     brms,
     car,
     cluster,

R/sjPlotAnova.R

@@ -76,9 +76,9 @@ sjp.aov1 <- function(var.dep,
   # --------------------------------------------------------
   # remove titles if empty
   # --------------------------------------------------------
-  if (!is.null(axis.labels) && axis.labels == "") axis.labels <- NULL
-  if (!is.null(axis.title) && axis.title == "") axis.title <- NULL
-  if (!is.null(title) && title == "") title <- NULL
+  if (!is.null(axis.labels) && length(axis.labels) == 1 && axis.labels == "") axis.labels <- NULL
+  if (!is.null(axis.title) && length(axis.title) == 1 && axis.title == "") axis.title <- NULL
+  if (!is.null(title) && length(title) == 1 && title == "") title <- NULL
   # --------------------------------------------------------
   # unlist labels
   # --------------------------------------------------------

R/sjPlotSetTheme.R

@@ -560,7 +560,7 @@ sj.setGeomColors <- function(plot,
   # ---------------------------------------------------------
   # check for themr options
   # ---------------------------------------------------------
-  if (!is.null(geom.colors) && geom.colors == "themr") {
+  if (!is.null(geom.colors) && geom.colors[1] == "themr") {
     return(plot)
   }
 

R/sjTabSPSS.R

@@ -38,7 +38,7 @@
 #' @param max.len Numeric, indicates how many values and value labels per variable
 #'   are shown. Useful for variables with many different values, where the output
 #'   can be truncated.
-#' @param verbose,hide.progress Logical, if \code{TRUE}, a progress bar is displayed
+#' @param verbose Logical, if \code{TRUE}, a progress bar is displayed
 #'   while creating the output.
 #'
 #' @inheritParams tab_df
@@ -97,21 +97,13 @@ view_df <- function(x,
                     max.len = 15,
                     sort.by.name = FALSE,
                     wrap.labels = 50,
-                    hide.progress = FALSE,
                     verbose = TRUE,
                     CSS = NULL,
                     encoding = NULL,
                     file = NULL,
                     use.viewer = TRUE,
                     remove.spaces = TRUE) {
 
-  ## TODO remove hide.progress later
-
-  if (!missing(hide.progress)) {
-    message("`hide.progress` is deprecated. Please use `verbose` instead.")
-    verbose <- !hide.progress
-  }
-
   # check encoding
   encoding <- get.encoding(encoding, x)
 

R/sjTabStackFrq.R

@@ -146,7 +146,7 @@ sjt.stackfrq <- function(items,
     value.labels <- sjlabelled::get_labels(
       items[[1]],
       attr.only = F,
-      values = NULL,
+      values = "n",
       non.labelled = T
     )
   }
@@ -165,7 +165,7 @@ sjt.stackfrq <- function(items,
   # ----------------------------
   if (is.null(value.labels)) value.labels <- as.character(minval:maxval)
   # check whether missings should be shown
-  if (show.na) value.labels <- c(value.labels, string.na)
+  if (show.na) value.labels <- c(value.labels, `NA` = string.na)
   # save amolunt of values
   catcount <- length(value.labels)
   # check length of x-axis-labels and split longer strings at into new lines

R/tab_model.R

@@ -307,7 +307,7 @@ tab_model <- function(
 
   models <- list(...)
 
-  if (length(class(models[[1]]) == 1) && class(models[[1]]) == "list")
+  if (length(class(models[[1]])) == 1 && class(models[[1]]) == "list")
     models <- lapply(models[[1]], function(x) x)
 
   names(models) <- unlist(lapply(

R/tidiers.R

@@ -257,6 +257,8 @@ tidy_stan_model <- function(model, ci.lvl, tf, type, bpe, show.zeroinf, facets,
       dat <- dplyr::slice(dat, !! -resp.cor)
   }
 
+  # do transformation on posterior samples first,
+  # then summarize (see https://discourse.mc-stan.org/t/monotonic-effects-in-non-gaussian-models/6353/5)
 
   # need to transform point estimate as well
   if (!is.null(tf)) {

README.md

@@ -11,8 +11,8 @@ Collection of plotting and table output functions for data visualization. Result
 To install the latest development snapshot (see latest changes below), type following commands into the R console:
 
 ```r
-library(githubinstall)
-githubinstall::githubinstall("sjPlot")
+library(devtools)
+devtools::install_github("sjPlot")
 ```
 
 Please note the package dependencies when installing from GitHub. The GitHub version of this package may depend on latest GitHub versions of my other packages, so you may need to install those first, if you encounter any problems. Here's the order for installing packages from GitHub: