ci = NULL suppresses confidence intervals and SE

DESCRIPTION

@@ -1,7 +1,7 @@
 Type: Package
 Package: modelbased
 Title: Estimation of Model-Based Predictions, Contrasts and Means
-Version: 0.16.0
+Version: 0.16.0.1
 Authors@R:
     c(person(given = "Dominique",
              family = "Makowski",

NEWS.md

@@ -1,3 +1,10 @@
+# modelbased (devel)
+
+## Changes
+
+* `ci = NULL` now suppresses calculation of standard errors and confidence
+  intervals.
+
 # modelbased 0.16.0
 
 ## Changes

R/estimate_means.R

@@ -115,6 +115,9 @@
 #' number, only as many columns as indicated in `keep_iterations` will be added
 #' to the output. You can reshape them to a long format by running
 #' [`bayestestR::reshape_iterations()`].
+#' @param ci Confidence Interval (CI) level. Must be numeric between 0 and 1.
+#' Defaults to `0.95`. Use `NULL` to suppress calculation of standard errors and
+#' confidence intervals.
 #' @param verbose Use `FALSE` to silence messages and warnings.
 #' @param ... Other arguments passed, for instance, to [insight::get_datagrid()],
 #' to functions from the **emmeans** or **marginaleffects** package, or to process
@@ -151,9 +154,6 @@
 #'   `estimate = "population"` without specifying the `offset`, to average
 #'   predictions over the distribution of the offset (if appropriate).
 #'
-#' @inheritParams parameters::model_parameters.default
-#' @inheritParams estimate_expectation
-#'
 #' @details
 #' The [estimate_slopes()], [estimate_means()] and [estimate_contrasts()]
 #' functions are forming a group, as they are all based on *marginal*

R/get_marginalmeans.R

@@ -184,6 +184,12 @@ get_marginalmeans <- function(
     fun_args$re.form <- NULL
   }
 
+  # missing or NA for conf_level? If so, we want to suppress SE and CI
+  if (is.null(fun_args$conf_level) || is.na(fun_args$conf_level)) {
+    fun_args$conf_level <- NULL # for NA
+    fun_args$vcov <- FALSE
+  }
+
   # transform reponse?
   if (isTRUE(transform)) {
     transform <- insight::get_transformation(model, verbose = FALSE)$inverse

R/get_marginaltrends.R

@@ -129,6 +129,12 @@ get_marginaltrends <- function(
     fun_args$type <- predict
   }
 
+  # missing or NA for conf_level? If so, we want to suppress SE and CI
+  if (is.null(fun_args$conf_level) || is.na(fun_args$conf_level)) {
+    fun_args$conf_level <- NULL # for NA
+    fun_args$vcov <- FALSE
+  }
+
   # Third step: compute marginal slopes ---------------------------------------
   # ---------------------------------------------------------------------------
 

tests/testthat/test-estimate_means_ci.R

@@ -15,22 +15,56 @@ test_that("estimate_means() - ci frequentist", {
   x <- capture.output(out)
   expect_identical(x[5], "setosa     | 4.75 | 0.09 | [4.61, 4.89] |  54.34")
 
-  out <- estimate_contrasts(mod2, contrast = "Species", backend = "marginaleffects", ci = 0.95)
+  out <- estimate_contrasts(
+    mod2,
+    contrast = "Species",
+    backend = "marginaleffects",
+    ci = 0.95
+  )
   x <- capture.output(out)
-  expect_identical(x[5], "versicolor | setosa     |       1.43 | 0.12 | [1.19, 1.68] |  11.78 | < .001")
-
-  out <- estimate_contrasts(mod2, contrast = "Species", backend = "marginaleffects", ci = 0.89)
+  expect_identical(
+    x[5],
+    "versicolor | setosa     |       1.43 | 0.12 | [1.19, 1.68] |  11.78 | < .001"
+  )
+
+  out <- estimate_contrasts(
+    mod2,
+    contrast = "Species",
+    backend = "marginaleffects",
+    ci = 0.89
+  )
   x <- capture.output(out)
-  expect_identical(x[5], "versicolor | setosa     |       1.43 | 0.12 | [1.24, 1.63] |  11.78 | < .001")
+  expect_identical(
+    x[5],
+    "versicolor | setosa     |       1.43 | 0.12 | [1.24, 1.63] |  11.78 | < .001"
+  )
 
   # Estimate slopes with different CIs
-  out <- estimate_slopes(mod2, trend = "Sepal.Width", by = "Species", backend = "marginaleffects", ci = 0.95)
+  out <- estimate_slopes(
+    mod2,
+    trend = "Sepal.Width",
+    by = "Species",
+    backend = "marginaleffects",
+    ci = 0.95
+  )
   x <- capture.output(out)
   expect_identical(x[5], "setosa     |  0.69 | 0.17 | [0.36, 1.02] |   4.17 | < .001")
 
-  out <- estimate_slopes(mod2, trend = "Sepal.Width", by = "Species", backend = "marginaleffects", ci = 0.89)
+  out <- estimate_slopes(
+    mod2,
+    trend = "Sepal.Width",
+    by = "Species",
+    backend = "marginaleffects",
+    ci = 0.89
+  )
   x <- capture.output(out)
   expect_identical(x[5], "setosa     |  0.69 | 0.17 | [0.42, 0.96] |   4.17 | < .001")
+
+  # suppress CI
+  out <- estimate_means(mod2, by = "Species", backend = "marginaleffects", ci = NULL)
+  expect_named(out, c("Species", "Mean", "df"))
+  out <- estimate_means(mod2, by = "Species", backend = "marginaleffects", ci = NA)
+  expect_named(out, c("Species", "Mean", "df"))
 })
 
 
@@ -48,26 +82,66 @@ test_that("estimate_means() - ci frequentist", {
   # Estimate means with different CIs
   out <- estimate_means(mod2, by = "Species", backend = "marginaleffects", ci = 0.95)
   x <- capture.output(out)
-  expect_identical(x[5], "setosa     |   4.76 | [4.59, 4.93] | 100% | [-0.10, 0.10] |        0%")
+  expect_identical(
+    x[5],
+    "setosa     |   4.76 | [4.59, 4.93] | 100% | [-0.10, 0.10] |        0%"
+  )
 
   out <- estimate_means(mod2, by = "Species", backend = "marginaleffects", ci = 0.89)
   x <- capture.output(out)
-  expect_identical(x[5], "setosa     |   4.76 | [4.62, 4.90] | 100% | [-0.10, 0.10] |        0%")
-
-  out <- estimate_contrasts(mod2, contrast = "Species", backend = "marginaleffects", ci = 0.95)
+  expect_identical(
+    x[5],
+    "setosa     |   4.76 | [4.62, 4.90] | 100% | [-0.10, 0.10] |        0%"
+  )
+
+  out <- estimate_contrasts(
+    mod2,
+    contrast = "Species",
+    backend = "marginaleffects",
+    ci = 0.95
+  )
   x <- capture.output(out)
-  expect_identical(x[5], "versicolor | setosa     |   1.43 | [1.18, 1.67] | 100% | [-0.10, 0.10] |        0%")
-
-  out <- estimate_contrasts(mod2, contrast = "Species", backend = "marginaleffects", ci = 0.89)
+  expect_identical(
+    x[5],
+    "versicolor | setosa     |   1.43 | [1.18, 1.67] | 100% | [-0.10, 0.10] |        0%"
+  )
+
+  out <- estimate_contrasts(
+    mod2,
+    contrast = "Species",
+    backend = "marginaleffects",
+    ci = 0.89
+  )
   x <- capture.output(out)
-  expect_identical(x[5], "versicolor | setosa     |   1.43 | [1.23, 1.63] | 100% | [-0.10, 0.10] |        0%")
+  expect_identical(
+    x[5],
+    "versicolor | setosa     |   1.43 | [1.23, 1.63] | 100% | [-0.10, 0.10] |        0%"
+  )
 
   # Estimate slopes with different CIs
-  out <- estimate_slopes(mod2, trend = "Sepal.Width", by = "Species", backend = "marginaleffects", ci = 0.95)
+  out <- estimate_slopes(
+    mod2,
+    trend = "Sepal.Width",
+    by = "Species",
+    backend = "marginaleffects",
+    ci = 0.95
+  )
   x <- capture.output(out)
-  expect_identical(x[5], "setosa     |   0.67 | [0.35, 0.99] | 100% | [-0.10, 0.10] |        0%")
-
-  out <- estimate_slopes(mod2, trend = "Sepal.Width", by = "Species", backend = "marginaleffects", ci = 0.89)
+  expect_identical(
+    x[5],
+    "setosa     |   0.67 | [0.35, 0.99] | 100% | [-0.10, 0.10] |        0%"
+  )
+
+  out <- estimate_slopes(
+    mod2,
+    trend = "Sepal.Width",
+    by = "Species",
+    backend = "marginaleffects",
+    ci = 0.89
+  )
   x <- capture.output(out)
-  expect_identical(x[5], "setosa     |   0.67 | [0.41, 0.93] | 100% | [-0.10, 0.10] |        0%")
+  expect_identical(
+    x[5],
+    "setosa     |   0.67 | [0.41, 0.93] | 100% | [-0.10, 0.10] |        0%"
+  )
 })

tests/testthat/test-estimate_slopes.R

@@ -88,6 +88,12 @@ test_that("estimate_slopes", {
   )
   expect_named(estim2, c("Petal.Length", "Slope", "SE", "CI_low", "CI_high", "z", "p"))
 
+  # suppress CI
+  out <- suppressMessages(estimate_slopes(model, ci = NULL))
+  expect_named(out, "Slope")
+  out <- suppressMessages(estimate_slopes(model, ci = NA))
+  expect_named(out, "Slope")
+
   model <- lm(Petal.Length ~ poly(Sepal.Width, 4), data = iris)
 
   estim1 <- suppressMessages(estimate_slopes(