https://github.com/easystats/modelbased/issues/120

NEWS.md

@@ -6,6 +6,11 @@
   numeric predictors, which only allow to predict for values that are actually
   present in the data.
 
+## Bug fixes
+
+* Fixed issue with adding raw data points for plots from logistic regression
+  models, when the response variable was no factor with numeric levels.
+
 # ggeffects 1.1.0
 
 ## New supported models

R/plot.R

@@ -881,8 +881,14 @@ plot.ggalleffects <- function(x,
   # dots / lines for marginal effects
 
   if (!is.null(rawdat)) {
+    # recode binary response to numeric? if so, make sure it starts with 0
+    if (identical(attributes(x)$logistic, "1")) {
+      lowest <- 0
+    } else {
+      lowest <- NULL
+    }
     # make sure response is numeric
-    rawdat$response <- .factor_to_numeric(rawdat$response)
+    rawdat$response <- .factor_to_numeric(rawdat$response, lowest = lowest)
 
     # check if we have a group-variable with at least two groups
     if (.obj_has_name(rawdat, "group")) {