estimate_means(backend = "marginaleffects") not calculating marginal means

NAMESPACE

@@ -65,10 +65,14 @@ export(find_inversions)
 export(get_emcontrasts)
 export(get_emmeans)
 export(get_emtrends)
+export(get_marginalcontrasts)
 export(get_marginaleffects)
+export(get_marginalmeans)
 export(model_emcontrasts)
 export(model_emmeans)
 export(model_emtrends)
+export(model_marginalcontrasts)
+export(model_marginalmeans)
 export(print_md)
 export(reshape_grouplevel)
 export(smoothing)

R/estimate_contrasts.R

@@ -7,13 +7,13 @@
 #' @inheritParams estimate_means
 #' @inheritParams get_emcontrasts
 #' @param p_adjust The p-values adjustment method for frequentist multiple
-#'   comparisons. Can be one of "holm" (default), "tukey", "hochberg", "hommel",
-#'   "bonferroni", "BH", "BY", "fdr" or "none". See the p-value adjustment
-#'   section in the `emmeans::test` documentation.
+#'   comparisons. Can be one of `"holm"` (default), `"tukey"`, `"hochberg"`,
+#'   `"hommel"`, `"bonferroni"`, `"BH"`, `"BY"`, `"fdr"` or `"none"`. See the
+#'   p-value adjustment section in the `emmeans::test` documentation.
 #'
 #' @inherit estimate_slopes details
 #'
-#' @examplesIf require("lme4", quietly = TRUE) && require("emmeans", quietly = TRUE) && require("rstanarm", quietly = TRUE)
+#' @examplesIf all(insight::check_if_installed(c("lme4", "emmeans", "rstanarm"), quietly = TRUE))
 #' \dontrun{
 #' # Basic usage
 #' model <- lm(Sepal.Width ~ Species, data = iris)
@@ -34,9 +34,6 @@
 #' # Or with custom specifications
 #' estimate_contrasts(model, contrast = c("Species", "Petal.Width=c(1, 2)"))
 #'
-#' # Can fixate the numeric at a specific value
-#' estimate_contrasts(model, fixed = "Petal.Width")
-#'
 #' # Or modulate it
 #' estimate_contrasts(model, by = "Petal.Width", length = 4)
 #'
@@ -51,22 +48,24 @@
 #' model <- lme4::lmer(Sepal.Width ~ Species + (1 | Petal.Length_factor), data = data)
 #' estimate_contrasts(model)
 #'
-#' library(rstanarm)
-#'
 #' data <- mtcars
 #' data$cyl <- as.factor(data$cyl)
 #' data$am <- as.factor(data$am)
 #'
-#' model <- stan_glm(mpg ~ cyl * am, data = data, refresh = 0)
+#' model <- rstanarm::stan_glm(mpg ~ cyl * am, data = data, refresh = 0)
 #' estimate_contrasts(model)
-#' estimate_contrasts(model, fixed = "am")
+#' # fix `am` at value 1
+#' estimate_contrasts(model, by = c("cyl", "am='1'"))
 #'
-#' model <- stan_glm(mpg ~ cyl * wt, data = data, refresh = 0)
+#' model <- rstanarm::stan_glm(mpg ~ cyl * wt, data = data, refresh = 0)
 #' estimate_contrasts(model)
-#' estimate_contrasts(model, fixed = "wt")
 #' estimate_contrasts(model, by = "wt", length = 4)
 #'
-#' model <- stan_glm(Sepal.Width ~ Species + Petal.Width + Petal.Length, data = iris, refresh = 0)
+#' model <- rstanarm::stan_glm(
+#'   Sepal.Width ~ Species + Petal.Width + Petal.Length,
+#'   data = iris,
+#'   refresh = 0
+#' )
 #' estimate_contrasts(model, by = "Petal.Length", test = "bf")
 #' }
 #'
@@ -75,7 +74,6 @@
 estimate_contrasts <- function(model,
                                contrast = NULL,
                                by = NULL,
-                               fixed = NULL,
                                transform = "none",
                                ci = 0.95,
                                p_adjust = "holm",
@@ -85,7 +83,6 @@ estimate_contrasts <- function(model,
   estimated <- get_emcontrasts(model,
     contrast = contrast,
     by = by,
-    fixed = fixed,
     transform = transform,
     method = method,
     adjust = p_adjust,
@@ -142,7 +139,6 @@ estimate_contrasts <- function(model,
   attr(out, "transform") <- transform
   attr(out, "at") <- info$by
   attr(out, "by") <- info$by
-  attr(out, "fixed") <- info$fixed
   attr(out, "contrast") <- info$contrast
   attr(out, "p_adjust") <- p_adjust
 

R/estimate_means.R

@@ -19,7 +19,6 @@
 #' model <- lm(Petal.Length ~ Sepal.Width * Species, data = iris)
 #'
 #' estimate_means(model)
-#' estimate_means(model, fixed = "Sepal.Width")
 #' estimate_means(model, by = c("Species", "Sepal.Width"), length = 2)
 #' estimate_means(model, by = "Species=c('versicolor', 'setosa')")
 #' estimate_means(model, by = "Sepal.Width=c(2, 4)")
@@ -28,7 +27,7 @@
 #' estimate_means(model, by = "Sepal.Width=c(2, 4)")
 #'
 #' # Methods that can be applied to it:
-#' means <- estimate_means(model, fixed = "Sepal.Width")
+#' means <- estimate_means(model, by = c("Species", "Sepal.Width=0"))
 #'
 #' @examplesIf require("see") && require("emmeans", quietly = TRUE)
 #' plot(means) # which runs visualisation_recipe()
@@ -48,19 +47,18 @@
 #' @export
 estimate_means <- function(model,
                            by = "auto",
-                           fixed = NULL,
                            transform = "response",
                            ci = 0.95,
                            backend = "emmeans",
                            ...) {
   if (backend == "emmeans") {
     # Emmeans ------------------------------------------------------------------
-    estimated <- get_emmeans(model, by, fixed, transform = transform, ...)
+    estimated <- get_emmeans(model, by, transform = transform, ...)
     means <- .format_emmeans_means(estimated, model, ci, transform, ...)
   } else {
     # Marginalmeans ------------------------------------------------------------
-    estimated <- .get_marginalmeans(model, by, ci = ci, ...)
-    means <- .format_marginaleffects_means(estimated, model, ...)
+    estimated <- get_marginalmeans(model, by, transform = transform, ci = ci, ...)
+    means <- .format_marginaleffects_means(estimated, model, transform, ...)
   }
 
 

R/get_emcontrasts.R

@@ -1,43 +1,38 @@
 #' @rdname get_emmeans
 #'
 #' @param contrast A character vector indicating the name of the variable(s)
-#'   for which to compute the contrasts.
+#' for which to compute the contrasts.
 #' @param method Contrast method. See same argument in [emmeans::contrast].
 #'
-#' @examples
-#' if (require("emmeans", quietly = TRUE)) {
-#'   # Basic usage
-#'   model <- lm(Sepal.Width ~ Species, data = iris)
-#'   get_emcontrasts(model)
+#' @examplesIf insight::check_if_installed("emmeans", quietly = TRUE)
+#' # Basic usage
+#' model <- lm(Sepal.Width ~ Species, data = iris)
+#' get_emcontrasts(model)
 #'
-#'   # Dealing with interactions
-#'   model <- lm(Sepal.Width ~ Species * Petal.Width, data = iris)
-#'   # By default: selects first factor
-#'   get_emcontrasts(model)
-#'   # Can also run contrasts between points of numeric
-#'   get_emcontrasts(model, contrast = "Petal.Width", length = 3)
-#'   # Or both
-#'   get_emcontrasts(model, contrast = c("Species", "Petal.Width"), length = 2)
-#'   # Or with custom specifications
-#'   estimate_contrasts(model, contrast = c("Species", "Petal.Width=c(1, 2)"))
-#'   # Can fixate the numeric at a specific value
-#'   get_emcontrasts(model, fixed = "Petal.Width")
-#'   # Or modulate it
-#'   get_emcontrasts(model, by = "Petal.Width", length = 4)
-#' }
+#' # Dealing with interactions
+#' model <- lm(Sepal.Width ~ Species * Petal.Width, data = iris)
+#' # By default: selects first factor
+#' get_emcontrasts(model)
+#' # Can also run contrasts between points of numeric
+#' get_emcontrasts(model, contrast = "Petal.Width", length = 3)
+#' # Or both
+#' get_emcontrasts(model, contrast = c("Species", "Petal.Width"), length = 2)
+#' # Or with custom specifications
+#' estimate_contrasts(model, contrast = c("Species", "Petal.Width=c(1, 2)"))
+#' # Or modulate it
+#' get_emcontrasts(model, by = "Petal.Width", length = 4)
 #' @export
 get_emcontrasts <- function(model,
                             contrast = NULL,
                             by = NULL,
-                            fixed = NULL,
                             transform = "none",
                             method = "pairwise",
                             ...) {
   # check if available
   insight::check_if_installed("emmeans")
 
   # Guess arguments
-  my_args <- .guess_emcontrasts_arguments(model, contrast, by, fixed, ...)
+  my_args <- .guess_emcontrasts_arguments(model, contrast, by, ...)
 
   # Run emmeans
   estimated <- emmeans::emmeans(
@@ -57,7 +52,6 @@ get_emcontrasts <- function(model,
   attr(out, "contrast") <- my_args$contrast
   attr(out, "at") <- my_args$by
   attr(out, "by") <- my_args$by
-  attr(out, "fixed") <- my_args$fixed
   out
 }
 
@@ -74,7 +68,6 @@ model_emcontrasts <- get_emcontrasts
 .guess_emcontrasts_arguments <- function(model,
                                          contrast = NULL,
                                          by = NULL,
-                                         fixed = NULL,
                                          ...) {
   # Gather info
   predictors <- insight::find_predictors(model, effects = "fixed", flatten = TRUE, ...)
@@ -91,6 +84,6 @@ model_emcontrasts <- get_emcontrasts
     contrast <- predictors
   }
 
-  my_args <- list(contrast = contrast, by = by, fixed = fixed)
+  my_args <- list(contrast = contrast, by = by)
   .format_emmeans_arguments(model, args = my_args, data = model_data, ...)
 }

R/get_emmeans.R

@@ -8,22 +8,18 @@
 #' functions.
 #'
 #' @param model A statistical model.
-#' @param fixed A character vector indicating the names of the predictors to be
-#'   "fixed" (i.e., maintained), so that the estimation is made at these values.
-#' @param transform Is passed to the `type` argument in
-#'   `emmeans::emmeans()`. See
-#'   [this vignette](https://CRAN.R-project.org/package=emmeans/vignettes/transformations.html).
-#'   Can be `"none"` (default for contrasts), `"response"`
-#'   (default for means), `"mu"`, `"unlink"`, `"log"`.
-#'   `"none"` will leave the values on scale of the linear predictors.
-#'   `"response"` will transform them on scale of the response variable.
-#'   Thus for a logistic model, `"none"` will give estimations expressed in
-#'   log-odds (probabilities on logit scale) and `"response"` in terms of
-#'   probabilities.
+#' @param transform Is passed to the `type` argument in `emmeans::emmeans()`.
+#' See [this vignette](https://CRAN.R-project.org/package=emmeans/vignettes/transformations.html).
+#' Can be `"none"` (default for contrasts), `"response"` (default for means),
+#' `"mu"`, `"unlink"`, `"log"`. `"none"` will leave the values on scale of the
+#' linear predictors. `"response"` will transform them on scale of the response
+#' variable. Thus for a logistic model, `"none"` will give estimations expressed
+#' in log-odds (probabilities on logit scale) and `"response"` in terms of
+#' probabilities.
 #' @param by The predictor variable(s) at which to evaluate the desired effect
-#'   / mean / contrasts. Other predictors of the model that are not included
-#'   here will be collapsed and "averaged" over (the effect will be estimated
-#'   across them).
+#' / mean / contrasts. Other predictors of the model that are not included
+#' here will be collapsed and "averaged" over (the effect will be estimated
+#' across them).
 #' @param ... Other arguments passed for instance to [insight::get_datagrid()].
 #'
 #' @examples
@@ -49,14 +45,13 @@
 #' @export
 get_emmeans <- function(model,
                         by = "auto",
-                        fixed = NULL,
                         transform = "response",
                         ...) {
   # check if available
   insight::check_if_installed("emmeans")
 
   # Guess arguments
-  my_args <- .guess_emmeans_arguments(model, by, fixed, ...)
+  my_args <- .guess_emmeans_arguments(model, by, ...)
 
 
   # Run emmeans
@@ -78,7 +73,6 @@ get_emmeans <- function(model,
 
   attr(estimated, "at") <- my_args$by
   attr(estimated, "by") <- my_args$by
-  attr(estimated, "fixed") <- my_args$fixed
   estimated
 }
 
@@ -91,7 +85,7 @@ model_emmeans <- get_emmeans
 # =========================================================================
 # HELPERS  ----------------------------------------------------------------
 # =========================================================================
-# This function is the actual equivalent of .get_marginalmeans(); both being used
+# This function is the actual equivalent of get_marginalmeans(); both being used
 # in estimate_means
 
 #' @keywords internal
@@ -122,7 +116,6 @@ model_emmeans <- get_emmeans
 
   attr(means, "at") <- info$by
   attr(means, "by") <- info$by
-  attr(means, "fixed") <- info$fixed
   means
 }
 
@@ -135,7 +128,6 @@ model_emmeans <- get_emmeans
 #' @keywords internal
 .guess_emmeans_arguments <- function(model,
                                      by = NULL,
-                                     fixed = NULL,
                                      ...) {
   # Gather info
   predictors <- insight::find_predictors(model, effects = "fixed", flatten = TRUE, ...)
@@ -150,7 +142,7 @@ model_emmeans <- get_emmeans
     insight::format_alert(paste0("We selected `by = c(", toString(paste0('"', by, '"')), ")`."))
   }
 
-  my_args <- list(by = by, fixed = fixed)
+  my_args <- list(by = by)
   .format_emmeans_arguments(model, args = my_args, data = my_data, ...)
 }
 
@@ -177,7 +169,6 @@ model_emmeans <- get_emmeans
   } else {
     if (!is.null(args$by) && all(args$by == "all")) {
       target <- insight::find_predictors(model, effects = "fixed", flatten = TRUE)
-      target <- target[!target %in% args$fixed]
     } else {
       target <- args$by
     }
@@ -200,16 +191,6 @@ model_emmeans <- get_emmeans
     }
   }
 
-  # Deal with 'fixed'
-  if (!is.null(args$fixed)) {
-    fixed <- insight::get_datagrid(data[args$fixed], by = NULL, ...)
-    if (is.null(args$data_matrix)) {
-      args$data_matrix <- fixed
-    } else {
-      args$data_matrix <- merge(args$data_matrix, fixed)
-    }
-  }
-
   # Get 'specs' and 'at'
   # --------------------
   if (is.null(args$data_matrix)) {

R/get_emtrends.R

@@ -20,13 +20,12 @@
 get_emtrends <- function(model,
                          trend = NULL,
                          by = NULL,
-                         fixed = NULL,
                          ...) {
   # check if available
   insight::check_if_installed("emmeans")
 
   # Guess arguments
-  my_args <- .guess_emtrends_arguments(model, trend, by, fixed, ...)
+  my_args <- .guess_emtrends_arguments(model, trend, by, ...)
 
   # Run emtrends
   estimated <- emmeans::emtrends(
@@ -40,7 +39,6 @@ get_emtrends <- function(model,
   attr(estimated, "trend") <- my_args$trend
   attr(estimated, "at") <- my_args$by
   attr(estimated, "by") <- my_args$by
-  attr(estimated, "fixed") <- my_args$fixed
   estimated
 }
 
@@ -56,7 +54,6 @@ model_emtrends <- get_emtrends
 .guess_emtrends_arguments <- function(model,
                                       trend = NULL,
                                       by = NULL,
-                                      fixed = NULL,
                                       ...) {
   # Gather info
   predictors <- insight::find_predictors(model, effects = "fixed", flatten = TRUE, ...)
@@ -75,6 +72,6 @@ model_emtrends <- get_emtrends
     trend <- trend[1]
   }
 
-  my_args <- list(trend = trend, by = by, fixed = fixed)
+  my_args <- list(trend = trend, by = by)
   .format_emmeans_arguments(model, args = my_args, data = model_data, ...)
 }