Merge branch 'main' into paper

easystats · Feb 11, 2025 · 034e8e5 · 034e8e5
2 parents 7ca3a07 + 95ba671
commit 034e8e5
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diff --git a/DESCRIPTION b/DESCRIPTION
@@ -1,7 +1,7 @@
 Type: Package
 Package: modelbased
 Title: Estimation of Model-Based Predictions, Contrasts and Means
-Version: 0.9.0.13
+Version: 0.9.0.14
 Authors@R:
     c(person(given = "Dominique",
              family = "Makowski",

diff --git a/R/estimate_means.R b/R/estimate_means.R
@@ -188,7 +188,7 @@ estimate_means <- function(model,
   # validate input
   estimate <- insight::validate_argument(
     estimate,
-    c("average", "population", "specific")
+    c("average", "population", "specific", "sample")
   )
 
   if (backend == "emmeans") {

diff --git a/R/get_marginalmeans.R b/R/get_marginalmeans.R
@@ -41,7 +41,7 @@ get_marginalmeans <- function(model,
   # validate input
   estimate <- insight::validate_argument(
     estimate,
-    c("average", "population", "specific")
+    c("average", "population", "specific", "sample")
   )
 
   # model details
@@ -126,7 +126,7 @@ get_marginalmeans <- function(model,
     fun_args$variables <- lapply(datagrid, unique)[datagrid_info$at_specs$varname]
   } else {
     # all other "marginalizations"
-    if (is.null(dots$newdata)) {
+    if (is.null(dots$newdata) && estimate != "sample") {
       # we allow individual "newdata" options, so do not
       # # overwrite if explicitly set
       fun_args$newdata <- datagrid
@@ -181,6 +181,13 @@ get_marginalmeans <- function(model,
   # just need to add "hypothesis" argument
   means <- .call_marginaleffects(fun_args)
 
+  # filter "by" rows when we have "sample" marginalization, because we don't
+  # pass data grid in such situations
+  if (identical(estimate, "sample") && all(datagrid_info$at_specs$varname %in% colnames(means))) {
+    means <- datawizard::data_match(means, datagrid[datagrid_info$at_specs$varname])
+  }
+
+
   # =========================================================================
   # only needed to estimate_contrasts() with custom hypothesis ==============
   # =========================================================================

diff --git a/tests/testthat/test-estimate_contrasts.R b/tests/testthat/test-estimate_contrasts.R
@@ -728,3 +728,14 @@ test_that("estimate_contrasts - test all combinations of contrast and by, with f
   expect_snapshot(print(estimate_contrasts(model2, "time=c(1,2)", by = "grp"), zap_small = TRUE, table_width = Inf)) # nolint
   expect_snapshot(print(estimate_contrasts(model2, c("grp", "time=2")), zap_small = TRUE, table_width = Inf)) # nolint
 })
+
+
+test_that("estimate_contrast, full averaging", {
+  data(efc, package = "modelbased")
+  efc <- datawizard::to_factor(efc, c("c161sex", "c172code", "e16sex", "e42dep"))
+  levels(efc$c172code) <- c("low", "mid", "high")
+  m <- lm(neg_c_7 ~ c12hour + barthtot + e42dep + c161sex * c172code, data = efc)
+
+  out <- estimate_contrasts(m, "c161sex", by = "c172code", estimate = "sample")
+  expect_equal(out$Difference, c(1.09591, 0.68736, 0.92224), tolerance = 1e-4)
+})
diff --git a/tests/testthat/test-estimate_means.R b/tests/testthat/test-estimate_means.R
@@ -404,3 +404,26 @@ test_that("estimate_means, values inside correct bounds", {
   expect_true(all(out2$CI_low >= 0 & out2$CI_low <= 1))
   expect_true(all(out2$CI_high >= 0 & out2$CI_high <= 1))
 })
+
+
+test_that("estimate_means, full averaging", {
+  data(efc, package = "modelbased")
+  efc <- datawizard::to_factor(efc, c("c161sex", "c172code", "e16sex", "e42dep"))
+  levels(efc$c172code) <- c("low", "mid", "high")
+  m <- lm(neg_c_7 ~ c12hour + barthtot + e42dep + c161sex * c172code, data = efc)
+
+  estim1 <- marginaleffects::avg_predictions(m, by = c("c161sex", "c172code"))
+  estim2 <- estimate_means(m, by = c("c161sex", "c172code"), estimate = "sample")
+  expect_equal(estim1$estimate, estim2$Mean, tolerance = 1e-4)
+
+  estim1 <- marginaleffects::avg_predictions(m, variables = c("c161sex", "c172code"))
+  estim2 <- estimate_means(m, by = c("c161sex", "c172code"), estimate = "population")
+  expect_equal(estim1$estimate, estim2$Mean, tolerance = 1e-4)
+
+  estim1 <- marginaleffects::avg_predictions(m, newdata = "balanced", by = c("c161sex", "c172code"))
+  estim2 <- estimate_means(m, by = c("c161sex", "c172code"), estimate = "average")
+  expect_equal(estim1$estimate, estim2$Mean, tolerance = 1e-4)
+
+  estim2 <- estimate_means(m, by = c("c161sex", "c172code='mid'"), estimate = "sample")
+  expect_identical(dim(estim2), c(6L, 8L))
+})