prepare CRAN release

DESCRIPTION

@@ -2,8 +2,8 @@ Package: sjPlot
 Type: Package
 Encoding: UTF-8
 Title: Data Visualization for Statistics in Social Science
-Version: 2.5.0.9000
-Date: 2018-07-23
+Version: 2.6.0
+Date: 2018-08-23
 Authors@R: c(
     person("Daniel", "Lüdecke", email = "[email protected]", role = c("aut", "cre"), comment = c(ORCID = "0000-0002-8895-3206")),
     person("Carsten", "Schwemmer", email = "[email protected]", role = "ctb")

NEWS.md

@@ -32,7 +32,6 @@ Following functions are now defunct:
 
 * Due to changes in the _broom_ and _lmerTest_ packages, tidiers did no longer work for `lmerModLmerTest` objects.
 * Fix issue with standardized coefficient (argument `show.std`) in `tab_model()`.
-* Argument `dot.size` and `line.size` in `plot_model()` now also apply to marginal effects plots.
 
 # sjPlot 2.5.0
 

R/plot_gpt.R

@@ -1,3 +1,5 @@
+utils::globalVariables("n")
+
 #' @title Plot grouped proportional tables
 #' @name plot_gpt
 #'
@@ -254,8 +256,6 @@ gpt_helper <- function(
   # and summarize N per group and chisq.test
   # of grp and x within each group
 
-  ## TODO fix n() warning
-
   pvals <- mydf %>%
     dplyr::group_by(.data$grp) %>%
     dplyr::summarise(N = n(), p = suppressWarnings(stats::chisq.test(table(.data$xpos, .data$dep))$p.value))

R/plot_type_eff.R

@@ -66,9 +66,12 @@ plot_type_eff <- function(type,
     dot.alpha = dot.alpha,
     alpha = alpha,
     dodge = dodge,
-    log.y = log.y,
-    dot.size = dot.size,
-    line.size = line.size
+    log.y = log.y
+
+    ## TODO activate once ggeffects-update is on  CRAN
+
+    # dot.size = dot.size,
+    # line.size = line.size
   )
 
   # set axis and plot titles

R/plot_type_int.R

@@ -153,9 +153,12 @@ plot_type_int <- function(model,
       dot.alpha = dot.alpha,
       alpha = alpha,
       dodge = dodge,
-      log.y = log.y,
-      dot.size = dot.size,
-      line.size = line.size
+      log.y = log.y
+
+      ## TODO activate once ggeffects-update is on  CRAN
+
+      # dot.size = dot.size,
+      # line.size = line.size
     )
 
     # set axis and plot titles

R/sjPlotFrequencies.R

@@ -1,3 +1,5 @@
+utils::globalVariables("density")
+
 #' @title Plot frequencies of variables
 #' @name sjp.frq
 #'
@@ -509,9 +511,6 @@ sjp.frq <- function(var.cnt,
   } else if (type == "density") {
     # First, plot histogram with density curve
     baseplot <- ggplot(hist.dat, aes(x = .data$xv)) +
-
-      ## TODO use solution from new ggplot
-
       geom_histogram(aes(y = stat(density)), binwidth = geom.size, fill = geom.colors) +
       # transparent density curve above bars
       geom_density(aes(y = stat(density)), fill = "cornsilk", alpha = 0.3) +