add show_direction arg

NEWS.md

@@ -8,6 +8,9 @@
 - `plot()` for `model_parameters()` now also plots group-levels of random effects
   (i.e. for mixed models, when `model_parameters(x, ..., group_level = TRUE)`).
 
+- `plot()` for `model_parameters()` gets a `show_direction` argument, to turn
+  off the direction of the effect in the plot.
+
 - `plot()` for `simulate_parameters()` now better copes with models that have
   multiple response levels (e.g. multinomial models).
 

R/plot.parameters_model.R

@@ -21,6 +21,9 @@
 #' @param show_density Should the compatibility density (i.e., posterior,
 #'   bootstrap, or confidence density) of each parameter be shown?
 #'   (default: `FALSE`)
+#' @param show_direction Should the "direction" of coefficients (e.g., positive
+#' or negative coefficients) be highlighted using different colors?
+#' (default: `TRUE`)
 #' @param log_scale Should exponentiated coefficients (e.g., odds-ratios) be
 #'   plotted on a log scale? (default: `FALSE`)
 #' @param n_columns For models with multiple components (like fixed and random,
@@ -29,6 +32,14 @@
 #'
 #' @return A ggplot2-object.
 #'
+#' @note By default, coefficients and their confidence intervals are colored
+#' depending on whether they show a "positive" or "negative" association with
+#' the outcome. E.g., in case of linear models, colors simply distinguish positive
+#' or negative coefficients. For logistic regression models that are shown on the
+#' odds ratio scale, colors distinguish odds ratios above or below 1. Use
+#' `show_direction = FALSE` to disable this feature and only show a one-colored
+#' forest plot.
+#'
 #' @examples
 #' library(parameters)
 #' m <- lm(mpg ~ wt + cyl + gear + disp, data = mtcars)
@@ -48,6 +59,7 @@ plot.see_parameters_model <- function(x,
                                       show_estimate = TRUE,
                                       show_interval = TRUE,
                                       show_density = FALSE,
+                                      show_direction = TRUE,
                                       log_scale = FALSE,
                                       ...) {
   # retrieve settings ----------------
@@ -381,10 +393,20 @@ plot.see_parameters_model <- function(x,
       color_scale <- scale_color_material()
     }
 
-    p <- ggplot2::ggplot(x, ggplot2::aes(
-      y = .data$Parameter, x = .data$Coefficient,
-      size = rev(.data$CI), color = .data$group
-    )) +
+    # should positive/negative coefficients be highlighted?
+    if (show_direction) {
+      p <- ggplot2::ggplot(x, ggplot2::aes(
+        y = .data$Parameter, x = .data$Coefficient,
+        size = rev(.data$CI), color = .data$group
+      ))
+    } else {
+      p <- ggplot2::ggplot(x, ggplot2::aes(
+        y = .data$Parameter, x = .data$Coefficient,
+        size = rev(.data$CI)
+      ))
+    }
+
+    p <- p +
       ggplot2::geom_vline(ggplot2::aes(xintercept = y_intercept), linetype = "dotted") +
       theme_modern(legend.position = "none") +
       color_scale
@@ -416,10 +438,17 @@ plot.see_parameters_model <- function(x,
       color_scale <- scale_color_material()
     }
 
+    if (show_direction) {
     p <- ggplot2::ggplot(x, ggplot2::aes(y = .data$Parameter, x = .data$Coefficient, color = .data$group)) +
       ggplot2::geom_vline(ggplot2::aes(xintercept = y_intercept), linetype = "dotted") +
       theme_modern(legend.position = "none") +
       color_scale
+    } else {
+    p <- ggplot2::ggplot(x, ggplot2::aes(y = .data$Parameter, x = .data$Coefficient)) +
+      ggplot2::geom_vline(ggplot2::aes(xintercept = y_intercept), linetype = "dotted") +
+      theme_modern(legend.position = "none") +
+      color_scale
+    }
 
     if (show_density) {
       p <- p + density_layer

tests/testthat/test-plot.parameters_model.R

@@ -8,6 +8,10 @@ test_that("`plot.see_parameters_model()` works", {
     title = "plot.model_parameters_1",
     fig = plot(result)
   )
+  vdiffr::expect_doppelganger(
+    title = "plot.model_parameters_no_dir",
+    fig = plot(result, show_direction = FALSE)
+  )
 })
 
 test_that("`plot.see_parameters_model()` random parameters works", {