update

R/plot.parameters_model.R

@@ -613,6 +613,16 @@ plot.see_parameters_model <- function(x,
   min_ci <- min(x$CI_low, na.rm = TRUE)
   max_ci <- max(x$CI_high, na.rm = TRUE)
 
+  # here we check if all facets have the same scale. If so, we set the scales
+  # to fixed, otherwise we set them to free_y (in facet_wrap). This removes
+  # a redundant scale for plots with identical scales.
+  check_scales <- split(x$Level, x$Group)
+  if (isTRUE(identical(unname(check_scales[-length(check_scales)]), unname(check_scales[-1])))) {
+    facet_scales <- "fixed"
+  } else {
+    facet_scales <- "free_y"
+  }
+
   p <- ggplot2::ggplot(
     x,
     ggplot2::aes(
@@ -641,7 +651,7 @@ plot.see_parameters_model <- function(x,
       colour = "white",
       shape = 21
     ) +
-    ggplot2::facet_wrap(~Group, ncol = n_columns)
+    ggplot2::facet_wrap(~Group, ncol = n_columns, scales = facet_scales)
 
   # add coefficients and CIs?
   if (isTRUE(show_labels)) {

tests/testthat/test-plot.parameters_model.R

@@ -60,3 +60,23 @@ test_that("`plot.see_parameters_model()` random parameters works", {
     fig = plot(out, sort = "ascending", show_labels = TRUE, show_intercept = FALSE)
   )
 })
+
+
+test_that("`plot.see_parameters_model()` random parameters works", {
+  skip_if_not_installed("vdiffr")
+  skip_if_not_installed("lme4")
+  skip_if_not_installed("parameters")
+  data(sleepstudy, package = "lme4")
+
+  set.seed(12345)
+  sleepstudy$grp <- sample(1:5, size = 180, replace = TRUE)
+  model <- lmer(
+    Reaction ~ Days + (1 | grp) + (1 | Subject),
+    data = sleepstudy
+  )
+  out <- parameters::model_parameters(model, group_level = TRUE)
+  vdiffr::expect_doppelganger(
+    title = "plot.model_parameters_doublerandom",
+    fig = plot(out)
+  )
+})

vignettes/parameters.Rmd

@@ -148,6 +148,13 @@ result <- model_parameters(model2)
 plot(result)
 ```
 
+### Including group levels of random effects
+
+```{r}
+result <- model_parameters(model3, group_level = TRUE)
+plot(result)
+```
+
 ### Changing parameter names in the plot
 
 By default, `model_parameters()` returns a data frame, where the parameter names are found in the column `Parameter`. These names are used by default in the generated plot: