Fix issue with facet_grids and numeric predictors

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: modelbased
 Title: Estimation of Model-Based Predictions, Contrasts and Means
-Version: 0.8.9.29
+Version: 0.8.9.30
 Authors@R:
     c(person(given = "Dominique",
              family = "Makowski",

R/visualisation_recipe_internal.R

@@ -66,7 +66,13 @@
   }
   if (length(by) > 3) {
     aes$facet <- NULL
-    aes$grid <- stats::as.formula(paste(by[3], "~", paste(utils::tail(by, -3), collapse = "*")))
+    # we have to switch variables 3 and 4, due to regression formula
+    remaining <- paste(utils::tail(by, -2))
+    aes$grid <- stats::as.formula(paste(
+      remaining[2],
+      "~",
+      paste(setdiff(remaining, remaining[2]), collapse = "*")
+    ))
   }
 
   # CI
@@ -285,7 +291,7 @@
     stroke <- 1
   }
 
-  list(
+  out <- list(
     geom = geom,
     data = rawdata,
     aes = list(
@@ -296,8 +302,15 @@
     ),
     height = 0,
     shape = shape,
-    stroke = stroke,
-    # set default alpha, it not mapped by aes
-    alpha = ifelse(is.null(aes$alpha), 1 / 3, NULL)
+    stroke = stroke
   )
+
+  # set default alpha, it not mapped by aes
+  if (is.null(aes$alpha)) {
+    out$alpha <- 1 / 3
+  } else {
+    out$alpha <- NULL
+  }
+
+  out
 }

tests/testthat/test-plot.R

@@ -371,3 +371,21 @@ test_that("plots, logistic regression", {
     plot(out)
   )
 })
+
+
+test_that("plots, 4-way with numeric", {
+  skip_if_not_installed("ggeffects")
+  data(efc, package = "ggeffects")
+  # make categorical
+  efc <- datawizard::to_factor(efc, c("c161sex", "c172code", "e16sex"))
+  levels(efc$c172code) <- c("low", "mid", "high")
+  m <- lm(neg_c_7 ~ e16sex + c161sex + c172code * barthtot + c12hour, data = efc)
+  by <- c("c12hour", "c161sex", "c172code", "barthtot = [fivenum]")
+  estim <- estimate_means(m, by = by, backend = "marginaleffects")
+  set.seed(123)
+  vdiffr::expect_doppelganger(
+    "plot-4way-numeric-1",
+    plot(estim, show_data = FALSE)
+  )
+
+})