From e905816b085e3ff6191612ae19f5fd195b13a93e Mon Sep 17 00:00:00 2001
From: Joseph Luchman <jluchman@gmail.com>
Date: Sat, 30 Apr 2022 08:45:49 -0500
Subject: [PATCH 1/3] initial commit performance to parameters

---
 DESCRIPTION                              |   5 +-
 NAMESPACE                                |   2 +
 R/dominance_analysis.R                   | 497 +++++++++++++++++++++++
 _pkgdown.yml                             |   1 +
 inst/WORDLIST                            |   6 +
 man/dominance_analysis.Rd                | 147 +++++++
 tests/testthat/test-dominance_analysis.R |  81 ++++
 7 files changed, 737 insertions(+), 2 deletions(-)
 create mode 100644 R/dominance_analysis.R
 create mode 100644 man/dominance_analysis.Rd
 create mode 100644 tests/testthat/test-dominance_analysis.R

diff --git a/DESCRIPTION b/DESCRIPTION
index 3e5e3612f..f0594ade5 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -75,8 +75,8 @@ Depends:
     R (>= 3.4)
 Imports:
     bayestestR (>= 0.11.5),
-    datawizard (>= 0.4.0.3),
-    insight (> 0.17.0),
+    datawizard (>= 0.4.0),
+    insight (>= 0.17.0),
     graphics,
     methods,
     stats,
@@ -103,6 +103,7 @@ Suggests:
     cluster,
     cplm,
     dbscan,
+    domir (>= 0.2.0),
     drc,
     DRR,
     effectsize (>= 0.6.0),
diff --git a/NAMESPACE b/NAMESPACE
index 67e61310b..8e20685b0 100644
--- a/NAMESPACE
+++ b/NAMESPACE
@@ -544,6 +544,7 @@ S3method(print,n_clusters_silhouette)
 S3method(print,n_factors)
 S3method(print,parameters_brms_meta)
 S3method(print,parameters_clusters)
+S3method(print,parameters_da)
 S3method(print,parameters_efa)
 S3method(print,parameters_efa_summary)
 S3method(print,parameters_loadings)
@@ -867,6 +868,7 @@ export(dof_betwithin)
 export(dof_kenward)
 export(dof_ml1)
 export(dof_satterthwaite)
+export(dominance_analysis)
 export(efa_to_cfa)
 export(equivalence_test)
 export(factor_analysis)
diff --git a/R/dominance_analysis.R b/R/dominance_analysis.R
new file mode 100644
index 000000000..492443b57
--- /dev/null
+++ b/R/dominance_analysis.R
@@ -0,0 +1,497 @@
+#' @title Dominance Analysis
+#' @name dominance_analysis
+#' @inheritParams domir::domin
+#'
+#' @description Computes Dominance Analysis Statistics and Designations
+#'
+#' @param model A model object supported by `performance::r2()`. See 'Details'.
+#' @param sets A (named) list of formula objects with no left hand
+#' side/response.  A named list uses the name provided each element
+#' as the label for the set.
+#'
+#' Predictors in each formula are bound together as a set in the dominance
+#' analysis and dominance statistics and designations are computed for
+#' the predictors together.  Predictors in `sets` must be present in the model
+#' submitted to the `model` argument and cannot be in the `all` argument.
+#' @param all A formula with no left hand side/response.
+#'
+#' Predictors in the formula are included in each subset in the dominance
+#' analysis and the R2 value associated with them is subtracted from the
+#' overall value.  Predictors in `all` must be present in the model
+#' submitted to the `model` argument and cannot be in the `sets` argument.
+#'
+#' @param quote_args A character vector of arguments in the model submitted to
+#' `model` to `quote()` prior to submitting to the dominance analysis.  This
+#' is necessary for data masked arguments (e.g., `weights`) to prevent them
+#' from being evaluated before being applied to the model and causing an error.
+#'
+#' @param ...  Not used at current.
+#'
+#' @return Object of class `"parameters_da"`.
+#'
+#' An object of class `"parameters_da"` is a list of `data.frame`s composed
+#' of the following elements:
+#' \describe{
+#'  \item{`general`}{A `data.frame` which associates dominance statistics with
+#'  model parameters. The variables in this `data.frame` include:
+#'   \describe{
+#'     \item{`parameter`}{Parameter names.}
+#'      \item{`general_dominance`}{Vector of general dominance statistics.}
+#'      \item{`standardized`}{Vector of general dominance statistics normalized
+#'      to sum to 1.}
+#'      \item{`ranks`}{Vector of ranks applied to the general dominance
+#'      statistics.}
+#'      \item{`subset`}{Names of the subset to which the parameter belongs in
+#'      the dominance analysis.  Each other `data.frame` will refer to these
+#'      subset names.}}}
+#'  \item{`conditional_dominance`}{A `data.frame` of conditional dominance
+#'  statistics.  Each observation represents a subset and each variable
+#'  represents an the average increment to R2 with a specific number of
+#'  subsets in the model.  `NULL` if `conditional` argument is `FALSE`.}
+#'  \item{`complete_dominance`}{A `data.frame` of complete dominance
+#'  designations. The subsets in the observations are compared to the
+#'  subsets referenced in each variable. Whether the subset
+#'  in each variable dominates the subset in each observation is
+#'  represented in the  logical value. `NULL` if `complete`
+#'  argument is `FALSE`..}
+#' }
+#'
+#' @details Computes two decompositions of the model's R2 and returns
+#' a matrix of designations from which predictor relative importance
+#' determinations can be obtained.
+#'
+#' Note in the output that the "constant" subset is associated with a
+#' component of the model that does not directly contribute to the R2 such
+#' as an intercept. The "all" subset is apportioned a component of the fit
+#' statistic but is not considered a part of the dominance analysis and
+#' therefore does not receive a rank, conditional dominance statistics, or
+#' complete dominance designations.
+#'
+#' The input model is parsed using `insight::find_predictors()`, does not
+#' yet support interactions, transformations, or offsets applied in the
+#' R formula, and will fail with an error if any such terms are detected.
+#'
+#' The model submitted must accept an formula object as a `formula`
+#' argument.  In addition, the model object must accept the data on which
+#' the model is estimated as a `data` argument.  Formulas submitted
+#' using object references (i.e., `lm(mtcars$mpg ~ mtcars$vs)`) and
+#' functions that accept data as a non-`data` argument
+#' (e.g., `survey::svyglm()` uses `design`) will fail with an error.
+#'
+#' Models that return `TRUE` for the `insight::model_info()`
+#' function's values "is_bayesian", "is_mixed", "is_gam",
+#' is_multivariate", "is_zero_inflated",
+#' or "is_hurdle" are not supported at current.
+#'
+#' When `performance::r2()` returns multiple values, only the first is used
+#' by default.
+#'
+#' The underlying `domir::domin()` function that implements the dominance
+#' statistic and designation computations has only been tested to R version
+#' 3.5 and will fail with an error if called in R versions < 3.5.
+#'
+#' @references
+#' - Azen, R., & Budescu, D. V. (2003). The dominance analysis approach
+#'   for comparing predictors in multiple regression. Psychological Methods,
+#'   8(2), 129-148. doi:10.1037/1082-989X.8.2.129
+#'
+#' - Budescu, D. V. (1993). Dominance analysis: A new approach to the
+#'   problem of relative importance of predictors in multiple regression.
+#'   Psychological Bulletin, 114(3), 542-551. doi:10.1037/0033-2909.114.3.542
+#'
+#' - Groemping, U. (2007). Estimators of relative importance in linear
+#'   regression based on variance decomposition. The American Statistician,
+#'   61(2), 139-147. doi:10.1198/000313007X188252
+#'
+#' @seealso [domir::domin()]
+#'
+#' @author Joseph Luchman
+#'
+#' @examples
+#' if (getRversion() >= "3.5.0" && require("domir") &&
+#' require("performance")) {
+#'   data(mtcars)
+#'   model <- glm(vs ~ cyl + carb + mpg, data = mtcars, family = binomial())
+#'
+#'   performance::r2(model)
+#'   dominance_analysis(model)
+#'}
+#' @export
+dominance_analysis <- function(model, sets = NULL, all = NULL,
+                               conditional = TRUE, complete = TRUE,
+                               quote_args = NULL, ...) {
+
+  # Exit Conditions ----
+  insight::check_if_installed("domir")
+  insight::check_if_installed("performance")
+
+  if (!insight::is_regression_model(model)) {
+    stop(insight::format_message(
+      paste(deparse(substitute(model)), "is not a supported insight model."),
+      "You may be able to dominance analyze this model using the domir package."
+    ), call. = FALSE)
+  }
+
+  if (!any(utils::.S3methods("r2", class = class(model)[[1]], envir = getNamespace("performance")) ==
+           paste0("r2.", class(model)[[1]]))) {
+    stop(insight::format_message(
+      paste(deparse(substitute(model)), "does not have a perfomance-supported r2 method."),
+      "You may be able to dominance analyze this model using the domir package."
+    ), call. = FALSE)
+  }
+
+  model_info <- insight::model_info(model)
+  if (any(unlist(model_info[c("is_bayesian", "is_mixed", "is_gam", "is_multivariate", "is_zero_inflated", "is_hurdle")]))) {
+    stop(insight::format_message(
+      paste0("`dominance_analysis()` does not yet support models of class ", class(model), "."),
+      "You may be able to dominance analyze this model using the domir package."
+    ), call. = FALSE)
+  }
+
+  if (!is.null(insight::find_interactions(model))) {
+    stop("Interactions in the model formula are not allowed.", call. = FALSE)
+  }
+
+  if (!all(insight::find_predictors(model)$conditional %in% attr(stats::terms(insight::find_formula(model)$conditional), "term.labels"))) {
+    stop(insight::format_message(
+      "Predictors do not match terms.",
+      "This usually occurs when there are in-formula predictor transformations such as log(x) or I(x+z)."
+    ), call. = FALSE)
+  }
+
+  if (!is.null(insight::find_offset(model))) {
+    stop("Offsets in the model formula are not allowed.", call. = FALSE)
+  }
+
+  if (getRversion() < "3.5") {
+    stop("R versions < 3.5 not supported.", call. = FALSE)
+  }
+
+  if (!is.null(sets)) {
+    if (!is.list(sets)) {
+      stop("sets argument must be submitted as list.", call. = FALSE)
+    }
+
+    if (length(sets) != length(unlist(sets))) {
+      stop("Nested lists are not allowed in sets.", call. = FALSE)
+    }
+
+    if (!all(sapply(sets, isa, "formula"))) {
+      stop("Each element of list in sets must be a formula.", call. = FALSE)
+    }
+
+    if (any(sapply(sets, function(x)  attr(stats::terms(x), "response")==1))) {
+      stop("Formulas in sets argument must not have responses/left hand sides.", call. = FALSE)
+    }
+  }
+
+  if (!is.null(all)) {
+    if (!isa(all, "formula")) {
+      stop("all argument must be submitted as a formula.", call. = FALSE)
+    }
+
+    if (attr(stats::terms(all), "response") == 1) {
+      stop("Formula in all argument must not have a response/left hand side.", call. = FALSE)
+    }
+  }
+
+  if (!is.null(quote_args) && !all(is.character(quote_args))) {
+    stop("All arguments in quote_args must be characters.", call. = FALSE)
+  }
+
+  # Collect components for arguments ----
+  ivs <- insight::find_predictors(model, flatten = TRUE)
+
+  dv <- insight::find_response(model)
+
+  reg <- insight::model_name(model)
+
+  # Process sets ----
+  if (!is.null(sets)) {
+    # gather predictors from each set
+    sets_processed <- lapply(sets, function(x) attr(stats::terms(x), "term.labels"))
+
+    # remove predictors from `ivs` list if in sets
+    set_remove_loc <- unlist(lapply(sets_processed, function(x) which(ivs %in% x)))
+
+    if (length(set_remove_loc) != length(unlist(sets_processed))) {
+      wrong_set_terms <- unlist(sets_processed)[which(!(unlist(sets_processed) %in% ivs))]
+
+      stop(
+        insight::format_message(
+          "Terms",
+          paste(wrong_set_terms, sep = " "),
+          "in sets argument do not match any predictors in model."), call. = FALSE)
+    }
+
+    ivs <- ivs[-set_remove_loc]
+
+    # apply names to sets
+    set_names <- names(sets)
+
+    missing_set_names <- which(set_names == "")
+
+    if (length(missing_set_names) > 0)
+      set_names[missing_set_names] <- paste0("set", missing_set_names)
+
+    if (any(set_names %in% c("all", "constant"))) {
+      stop(
+        insight::format_message(
+          "Names 'all' and 'constant' are reserved for subset names in the dominance_analysis function.",
+          "Please rename any sets currently named 'all' or 'constant.'"), call. = FALSE)
+    }
+
+    if (any(set_names %in% ivs)) {
+      repeat_names <- set_names[which(set_names %in% ivs)]
+
+      stop(insight::format_message(
+        "Set names",
+        paste(repeat_names, sep = " "), "are also the names of invidiual predictors.",
+           "Please rename these sets."), call. = FALSE)
+    }
+
+  }
+
+  else sets_processed <- NULL
+
+  # Process all ----
+  if (!is.null(all)) {
+    # gather predictors in all
+    all_processed <- attr(stats::terms(all), "term.labels")
+
+    # remove predictors in all from `ivs` list
+    all_remove_loc <-  which(ivs %in% all_processed)
+
+    if (any(all_processed %in% unlist(sets_processed))) {
+      reused_terms <- all_processed[which(all_processed %in% unlist(sets_processed))]
+
+      stop(insight::format_message(
+        "Terms",
+        paste(reused_terms, sep = " "),
+        "in all argument are also used in sets argument."), call. = FALSE)
+    }
+
+    if (length(all_remove_loc) != length(unlist(all_processed))) {
+      wrong_all_terms <- all_processed[which(!(all_processed) %in% ivs)]
+
+      stop(insight::format_message(
+        "Terms",
+        paste(wrong_all_terms, sep = " "),
+        "in all argument do not match any predictors in model."), call. = FALSE)
+    }
+
+    ivs <- ivs[-all_remove_loc] # update IVs
+
+  }
+
+  else all_processed <- NULL
+
+  # name collisions across subsets - exit
+  if (any(ivs %in% c("all", "constant"))) {
+    stop(
+      insight::format_message(
+        "Names 'all' and 'constant' are reserved for subset names in the dominance_analysis function.",
+        "Please rename any predictors currently named 'all' or 'constant.'",
+        "Alternatively, put the predictor in a set by itself."), call. = FALSE)
+  }
+
+  # big DA warning
+  if (length(c(ivs, unlist(sets_processed))) > 15) warning(
+    cat(paste("Total of", 2^length(ivs)-1, "models to be estimated.\n",
+              "Process may take some time.")) , call. = FALSE)
+
+  # Build non-formula model arguments to `domin` ----
+  fml <- stats::reformulate(ivs, response = dv, intercept = insight::has_intercept(model))
+
+  data <- insight::get_data(model)
+
+  args <- as.list(insight::get_call(model), collapse = "") # extract all arguments from call
+
+  loc <- which(!(names(args) %in% c("formula", "data"))) # find formula and data arguments
+
+  if (length(which(names(args) %in% c("formula", "data"))) != 2) { # exit if formula and data arguments missing
+    stop("Model submitted does not have a formula and data argument.", call. = FALSE)
+  }
+
+  args <- args[loc] # remove formula and data arguments
+  args <- args[-1] # remove function name
+
+  # quote arguments for domin
+  for (arg in quote_args) {
+    if (!(arg %in% names(args))) stop(arg, " in quote_args not among arguments in model.", call. = FALSE)
+
+    else args[[arg]] <- str2lang(paste0("quote(", deparse(args[[arg]]), ")", collapse = ""))
+
+  }
+
+  # Internal wrapper to ensure r2 values conform to domin ----
+  r2_wrap <- function(model, ...) {
+    list(fitstat = performance::r2(model, ...)[[1]])
+  }
+
+  # Finalize and implement DA
+  args2domin <- append(list(formula_overall = fml, reg = reg, fitstat = list(r2_wrap, "fitstat"),
+                    data = data, conditional = conditional, complete = complete,
+                    sets = sets_processed, all = all_processed), args)
+
+  utils::capture.output(domir_res <- do.call(domir::domin, args2domin))
+
+  # Set up returned data.frames ----
+  if (!is.null(sets)) {
+
+    names(domir_res$General_Dominance) <-
+      c(names(domir_res$General_Dominance)[1:(length(domir_res$General_Dominance) - length(set_names))],
+        set_names)
+
+    if (conditional)
+      rownames(domir_res$Conditional_Dominance) <- names(domir_res$General_Dominance)
+
+  }
+
+  if (complete) {
+
+    colnames(domir_res$Complete_Dominance) <- paste0("< ", names(domir_res$General_Dominance))
+
+    dimnames(domir_res$Complete_Dominance) <- list(
+      colnames(domir_res$Complete_Dominance),
+      names(domir_res$General_Dominance)
+    )
+
+    domir_res$Complete_Dominance <- t(domir_res$Complete_Dominance)
+
+  }
+
+  da_df_res <- da_df_cat <-
+    data.frame(parameter = insight::find_parameters(model, flatten = TRUE))
+
+  da_df_cat = data.frame(da_df_cat, subset = NA_character_)
+
+  if (!is.null(sets)) {
+
+    for (set in 1:length(sets)) {
+
+      set_name <- ifelse(!is.null(names(sets)[[set]]), names(sets)[[set]],
+                         paste0("set", set))
+
+      da_df_cat$subset <-
+        replace(da_df_cat$subset,
+                da_df_res$parameter %in% all.vars(sets[[set]]), set_name)
+
+    }
+
+  }
+
+  if (!is.null(all)) {
+
+      da_df_cat$subset <-
+        replace(da_df_cat$subset,
+                da_df_res$parameter %in% all.vars(all), "all")
+
+  }
+
+  da_df_cat$subset <-
+    ifelse((da_df_res$parameter %in% (insight::find_predictors(model, flatten = TRUE))) &
+             (is.na(da_df_cat$subset)),
+           da_df_res$parameter,
+           da_df_cat$subset)
+
+  da_df_cat$subset <-
+    replace(da_df_cat$subset,
+            is.na(da_df_cat$subset), "constant")
+
+  da_df_res <-
+    datawizard::data_merge(da_df_cat,
+                           data.frame(subset = names(domir_res$General_Dominance),
+                                      general_dominance = domir_res$General_Dominance))
+
+  if (!is.null(all)) {
+
+    da_df_res$general_dominance <-
+      replace(da_df_res$general_dominance, da_df_res$subset == "all", domir_res$Fit_Statistic_All_Subsets)
+
+  }
+
+  da_df_res <-
+    datawizard::data_merge(da_df_res,
+                           data.frame(subset = names(domir_res$General_Dominance),
+                                      standardized = domir_res$Standardized))
+
+  da_df_res <-
+    datawizard::data_merge(da_df_res,
+                           data.frame(subset = names(domir_res$General_Dominance),
+                                      ranks = domir_res$Ranks))
+
+  da_df_res <-
+    datawizard::data_relocate(da_df_res, "subset", after = "ranks")
+
+  if (conditional) {
+
+    da_df_cdl <-
+      data.frame(subset = names(domir_res$General_Dominance))
+
+    da_df_cdl <-
+      datawizard::data_merge(da_df_cdl,
+                             data.frame(subset = names(domir_res$General_Dominance),
+                                        domir_res$Conditional_Dominance))
+
+    da_df_cdl <-
+      datawizard::data_rename(da_df_cdl,
+                              names(da_df_cdl)[2:length(da_df_cdl)],
+                              colnames(domir_res$Conditional_Dominance))
+  }
+
+  else da_df_cdl <- NULL
+
+  if (complete) {
+
+  da_df_cpt <-
+    data.frame(subset = names(domir_res$General_Dominance))
+
+  da_df_cpt <-
+    datawizard::data_merge(da_df_cpt,
+                           data.frame(subset = names(domir_res$General_Dominance),
+                                      domir_res$Complete_Dominance))
+
+  da_df_cpt <-
+    datawizard::data_rename(da_df_cpt,
+                            names(da_df_cpt)[2:length(da_df_cpt)],
+                            colnames(domir_res$Complete_Dominance))
+
+  }
+
+  else da_df_cpt <- NULL
+
+  da_list <- list(general = da_df_res,
+                  conditional = da_df_cdl,
+                  complete = da_df_cpt)
+
+  # add attributes and class
+  attr(da_list, "model_R2") <- domir_res$Fit_Statistic_Overall
+  attr(da_list$general, "table_title") <- "General Dominance Statistics"
+  if (conditional) attr(da_list$conditional, "table_title") <- "Conditional Dominance Statistics"
+  if (complete) attr(da_list$complete, "table_title") <- "Complete Dominance Designations"
+
+  class(da_list) <- c("parameters_da")
+
+  da_list
+
+}
+
+
+
+
+# methods ------------------------------
+
+
+#' @export
+print.parameters_da <- function(x, digits = 3, ...) {
+  insight::print_color("# Dominance Analysis Results", "blue")
+  cat("\n\n")
+
+  cat("Model R2 Value: ", sprintf("%.*f", digits, attr(x, "model_R2")), "\n\n")
+
+  cat(insight::export_table(x, digits = digits, ...))
+
+  invisible(x)
+
+}
diff --git a/_pkgdown.yml b/_pkgdown.yml
index 10fa74936..c963408f9 100644
--- a/_pkgdown.yml
+++ b/_pkgdown.yml
@@ -25,6 +25,7 @@ reference:
 - title: "Comprehensive Model Parameters"
   contents:
   - compare_parameters
+  - dominance_analysis
   - model_parameters
   - model_parameters.aov
   - model_parameters.befa
diff --git a/inst/WORDLIST b/inst/WORDLIST
index 95b867c01..ee892714f 100644
--- a/inst/WORDLIST
+++ b/inst/WORDLIST
@@ -1,14 +1,17 @@
 Anova
+Azen
 BGGM
 BLUPs
 BMC
 BayesFM
 BayesFactor
+bayesian
 Bentler
 Bezdek
 Biometrics
 Biometrika
 Blume
+Budescu
 CFA
 CNG
 Cattell
@@ -18,6 +21,7 @@ Cramer's
 CrossValidated
 D'Agostino
 DBSCAN
+decompositions
 DOI
 DRR
 Davison
@@ -40,6 +44,7 @@ Garrido
 Gelman
 Golino
 Gorsuch
+Groemping
 Greevy
 Gustafson
 HC
@@ -61,6 +66,7 @@ LMMs
 Lakens
 Laparra
 Lawley
+Luchman
 MSA
 Maechler
 Malo
diff --git a/man/dominance_analysis.Rd b/man/dominance_analysis.Rd
new file mode 100644
index 000000000..ed7652121
--- /dev/null
+++ b/man/dominance_analysis.Rd
@@ -0,0 +1,147 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/dominance_analysis.R
+\name{dominance_analysis}
+\alias{dominance_analysis}
+\title{Dominance Analysis}
+\usage{
+dominance_analysis(
+  model,
+  sets = NULL,
+  all = NULL,
+  conditional = TRUE,
+  complete = TRUE,
+  quote_args = NULL,
+  ...
+)
+}
+\arguments{
+\item{model}{A model object supported by \code{performance::r2()}. See 'Details'.}
+
+\item{sets}{A (named) list of formula objects with no left hand
+side/response.  A named list uses the name provided each element
+as the label for the set.
+
+Predictors in each formula are bound together as a set in the dominance
+analysis and dominance statistics and designations are computed for
+the predictors together.  Predictors in \code{sets} must be present in the model
+submitted to the \code{model} argument and cannot be in the \code{all} argument.}
+
+\item{all}{A formula with no left hand side/response.
+
+Predictors in the formula are included in each subset in the dominance
+analysis and the R2 value associated with them is subtracted from the
+overall value.  Predictors in \code{all} must be present in the model
+submitted to the \code{model} argument and cannot be in the \code{sets} argument.}
+
+\item{conditional}{Logical.  If \code{FALSE} then conditional dominance matrix is not computed.
+
+If conditional dominance is not desired as an importance criterion, avoiding computing the conditional dominance matrix can save computation time.}
+
+\item{complete}{Logical.  If \code{FALSE} then complete dominance matrix is not computed.
+
+If complete dominance is not desired as an importance criterion, avoiding computing complete dominance designations can save computation time.}
+
+\item{quote_args}{A character vector of arguments in the model submitted to
+\code{model} to \code{quote()} prior to submitting to the dominance analysis.  This
+is necessary for data masked arguments (e.g., \code{weights}) to prevent them
+from being evaluated before being applied to the model and causing an error.}
+
+\item{...}{Not used at current.}
+}
+\value{
+Object of class \code{"parameters_da"}.
+
+An object of class \code{"parameters_da"} is a list of \code{data.frame}s composed
+of the following elements:
+\describe{
+\item{\code{general}}{A \code{data.frame} which associates dominance statistics with
+model parameters. The variables in this \code{data.frame} include:
+\describe{
+\item{\code{parameter}}{Parameter names.}
+\item{\code{general_dominance}}{Vector of general dominance statistics.}
+\item{\code{standardized}}{Vector of general dominance statistics normalized
+to sum to 1.}
+\item{\code{ranks}}{Vector of ranks applied to the general dominance
+statistics.}
+\item{\code{subset}}{Names of the subset to which the parameter belongs in
+the dominance analysis.  Each other \code{data.frame} will refer to these
+subset names.}}}
+\item{\code{conditional_dominance}}{A \code{data.frame} of conditional dominance
+statistics.  Each observation represents a subset and each variable
+represents an the average increment to R2 with a specific number of
+subsets in the model.  \code{NULL} if \code{conditional} argument is \code{FALSE}.}
+\item{\code{complete_dominance}}{A \code{data.frame} of complete dominance
+designations. The subsets in the observations are compared to the
+subsets referenced in each variable. Whether the subset
+in each variable dominates the subset in each observation is
+represented in the  logical value. \code{NULL} if \code{complete}
+argument is \code{FALSE}..}
+}
+}
+\description{
+Computes Dominance Analysis Statistics and Designations
+}
+\details{
+Computes two decompositions of the model's R2 and returns
+a matrix of designations from which predictor relative importance
+determinations can be obtained.
+
+Note in the output that the "constant" subset is associated with a
+component of the model that does not directly contribute to the R2 such
+as an intercept. The "all" subset is apportioned a component of the fit
+statistic but is not considered a part of the dominance analysis and
+therefore does not receive a rank, conditional dominance statistics, or
+complete dominance designations.
+
+The input model is parsed using \code{insight::find_predictors()}, does not
+yet support interactions, transformations, or offsets applied in the
+R formula, and will fail with an error if any such terms are detected.
+
+The model submitted must accept an formula object as a \code{formula}
+argument.  In addition, the model object must accept the data on which
+the model is estimated as a \code{data} argument.  Formulas submitted
+using object references (i.e., \code{lm(mtcars$mpg ~ mtcars$vs)}) and
+functions that accept data as a non-\code{data} argument
+(e.g., \code{survey::svyglm()} uses \code{design}) will fail with an error.
+
+Models that return \code{TRUE} for the \code{insight::model_info()}
+function's values "is_bayesian", "is_mixed", "is_gam",
+is_multivariate", "is_zero_inflated",
+or "is_hurdle" are not supported at current.
+
+When \code{performance::r2()} returns multiple values, only the first is used
+by default.
+
+The underlying \code{domir::domin()} function that implements the dominance
+statistic and designation computations has only been tested to R version
+3.5 and will fail with an error if called in R versions < 3.5.
+}
+\examples{
+if (getRversion() >= "3.5.0" && require("domir") &&
+require("performance")) {
+  data(mtcars)
+  model <- glm(vs ~ cyl + carb + mpg, data = mtcars, family = binomial())
+
+  performance::r2(model)
+  dominance_analysis(model)
+}
+}
+\references{
+\itemize{
+\item Azen, R., & Budescu, D. V. (2003). The dominance analysis approach
+for comparing predictors in multiple regression. Psychological Methods,
+8(2), 129-148. doi:10.1037/1082-989X.8.2.129
+\item Budescu, D. V. (1993). Dominance analysis: A new approach to the
+problem of relative importance of predictors in multiple regression.
+Psychological Bulletin, 114(3), 542-551. doi:10.1037/0033-2909.114.3.542
+\item Groemping, U. (2007). Estimators of relative importance in linear
+regression based on variance decomposition. The American Statistician,
+61(2), 139-147. doi:10.1198/000313007X188252
+}
+}
+\seealso{
+\code{\link[domir:domin]{domir::domin()}}
+}
+\author{
+Joseph Luchman
+}
diff --git a/tests/testthat/test-dominance_analysis.R b/tests/testthat/test-dominance_analysis.R
new file mode 100644
index 000000000..d9396ccbe
--- /dev/null
+++ b/tests/testthat/test-dominance_analysis.R
@@ -0,0 +1,81 @@
+if (requiet("testthat") && requiet("performance") && requiet("domir") &&
+    (R.version$major > 3 | (R.version$major == 3 && R.version$minor >= 5))) {
+
+  data(mtcars)
+
+  DA_test_model <- lm(mpg ~ vs + cyl + carb, data = mtcars)
+
+  DA_performance <- dominance_analysis(DA_test_model)
+
+  DA_domir <- domin(mpg ~ vs + cyl + carb, lm, list(performance::r2, "R2"), data = mtcars)
+
+  test_that("dominance_analysis$general_dominance", {
+
+    gnrl_domir <- c(NA, DA_domir$General_Dominance)
+    names(gnrl_domir) <- NULL
+
+    gnrl_da <- DA_performance$general$general_dominance
+
+    expect_equal(gnrl_domir,
+                 gnrl_da)
+  })
+
+  test_that("dominance_analysis$conditional_dominance", {
+
+    cdl_domir <- DA_domir$Conditional_Dominance
+    dimnames(cdl_domir) <-c(NULL, NULL)
+
+    cdl_da <- as.matrix(DA_performance$conditional[,-1])
+    dimnames(cdl_da) <-c(NULL, NULL)
+
+    expect_equal(cdl_domir,
+                 cdl_da)
+  })
+
+  test_that("dominance_analysis$complete_dominance", {
+
+    cpt_domir <- DA_domir$Complete_Dominance
+    dimnames(cpt_domir) <- list(NULL, NULL)
+
+    cpt_da <- t(DA_performance$complete[,-1])
+    dimnames(cpt_da) <- list(NULL, NULL)
+
+    expect_equal(cpt_domir,
+                 cpt_da)
+  })
+
+  DA_performance2 <-
+    dominance_analysis(DA_test_model, all = ~ vs,  sets = c(~carb),
+                       complete = FALSE, conditional = FALSE)
+  DA_domir2 <-
+    domin(mpg ~ cyl, lm, list(performance::r2, "R2"),
+          all = "vs", sets = list("carb"), data = mtcars,
+          complete = FALSE, conditional = FALSE)
+
+  test_that("dominance_analysis$general_dominance with sets/all", {
+
+    domir_all_sub_r2 <- DA_domir2$Fit_Statistic_All_Subsets
+    names(domir_all_sub_r2) <-NULL
+
+    expect_equal(domir_all_sub_r2,
+                 with(DA_performance2$general, general_dominance[subset == "all"]))
+
+    gnrl_domir2 <- DA_domir2$General_Dominance
+    names(gnrl_domir2) <- NULL
+
+    gnrl_da2 <- aggregate(DA_performance2$general$general_dominance,
+                          list(DA_performance2$general$subset), mean)
+
+    gnrl_da2 <- gnrl_da2[which(gnrl_da2$Group.1 %in% c("cyl", "set1")),]
+
+    gnrl_da2 <- gnrl_da2$x
+
+    names(gnrl_da2) <- NULL
+
+    expect_equal(gnrl_domir2,
+                 gnrl_da2)
+
+  })
+
+
+}

From 9baa6731cda7b26ed468f6b9f38378ec60d65ff4 Mon Sep 17 00:00:00 2001
From: Joseph Luchman <jluchman@gmail.com>
Date: Sun, 1 May 2022 09:57:11 -0500
Subject: [PATCH 2/3] documentation cleanup

---
 R/dominance_analysis.R    | 24 +++++++++++++++++++-----
 man/dominance_analysis.Rd | 19 ++++++++++++++++---
 2 files changed, 35 insertions(+), 8 deletions(-)

diff --git a/R/dominance_analysis.R b/R/dominance_analysis.R
index 492443b57..4630c3aa9 100644
--- a/R/dominance_analysis.R
+++ b/R/dominance_analysis.R
@@ -5,14 +5,17 @@
 #' @description Computes Dominance Analysis Statistics and Designations
 #'
 #' @param model A model object supported by `performance::r2()`. See 'Details'.
+#'
 #' @param sets A (named) list of formula objects with no left hand
-#' side/response.  A named list uses the name provided each element
-#' as the label for the set.
+#' side/response.  If the list has names, the name provided each element
+#' will be used as the label for the set.  Unnamed list elements will be
+#' provided a set number name based on its position among the sets as entered.
 #'
 #' Predictors in each formula are bound together as a set in the dominance
 #' analysis and dominance statistics and designations are computed for
 #' the predictors together.  Predictors in `sets` must be present in the model
 #' submitted to the `model` argument and cannot be in the `all` argument.
+#'
 #' @param all A formula with no left hand side/response.
 #'
 #' Predictors in the formula are included in each subset in the dominance
@@ -36,14 +39,16 @@
 #'  model parameters. The variables in this `data.frame` include:
 #'   \describe{
 #'     \item{`parameter`}{Parameter names.}
-#'      \item{`general_dominance`}{Vector of general dominance statistics.}
+#'      \item{`general_dominance`}{Vector of general dominance statistics.
+#'      The R2 ascribed to variables in the `all` argument are also reported
+#'      here though they are not general dominance statistics.}
 #'      \item{`standardized`}{Vector of general dominance statistics normalized
 #'      to sum to 1.}
 #'      \item{`ranks`}{Vector of ranks applied to the general dominance
 #'      statistics.}
 #'      \item{`subset`}{Names of the subset to which the parameter belongs in
-#'      the dominance analysis.  Each other `data.frame` will refer to these
-#'      subset names.}}}
+#'      the dominance analysis.  Each other `data.frame` returned will refer
+#'      to these subset names.}}}
 #'  \item{`conditional_dominance`}{A `data.frame` of conditional dominance
 #'  statistics.  Each observation represents a subset and each variable
 #'  represents an the average increment to R2 with a specific number of
@@ -111,10 +116,19 @@
 #' if (getRversion() >= "3.5.0" && require("domir") &&
 #' require("performance")) {
 #'   data(mtcars)
+#'
+#'   # Dominance Analysis with Logit Regression
 #'   model <- glm(vs ~ cyl + carb + mpg, data = mtcars, family = binomial())
 #'
 #'   performance::r2(model)
 #'   dominance_analysis(model)
+#'
+#'   # Dominance Analysis with Weighted Logit Regression
+#'   model_wt <- glm(vs ~ cyl + carb + mpg, data = mtcars,
+#'     weights = wt, family = binomial())
+#'
+#'  dominance_analysis(model_wt, quote_args = "weights")
+#'
 #'}
 #' @export
 dominance_analysis <- function(model, sets = NULL, all = NULL,
diff --git a/man/dominance_analysis.Rd b/man/dominance_analysis.Rd
index ed7652121..9960d0b52 100644
--- a/man/dominance_analysis.Rd
+++ b/man/dominance_analysis.Rd
@@ -18,8 +18,9 @@ dominance_analysis(
 \item{model}{A model object supported by \code{performance::r2()}. See 'Details'.}
 
 \item{sets}{A (named) list of formula objects with no left hand
-side/response.  A named list uses the name provided each element
-as the label for the set.
+side/response.  If the list has names, the name provided each element
+will be used as the label for the set.  Unnamed list elements will be
+provided a set number name based on its position among the sets as entered.
 
 Predictors in each formula are bound together as a set in the dominance
 analysis and dominance statistics and designations are computed for
@@ -58,7 +59,9 @@ of the following elements:
 model parameters. The variables in this \code{data.frame} include:
 \describe{
 \item{\code{parameter}}{Parameter names.}
-\item{\code{general_dominance}}{Vector of general dominance statistics.}
+\item{\code{general_dominance}}{Vector of general dominance statistics.
+The R2 ascribed to variables in the \code{all} argument are also reported
+here though they are not general dominance statistics.}
 \item{\code{standardized}}{Vector of general dominance statistics normalized
 to sum to 1.}
 \item{\code{ranks}}{Vector of ranks applied to the general dominance
@@ -120,10 +123,20 @@ statistic and designation computations has only been tested to R version
 if (getRversion() >= "3.5.0" && require("domir") &&
 require("performance")) {
   data(mtcars)
+
+  # Dominance Analysis with Logit Regression
   model <- glm(vs ~ cyl + carb + mpg, data = mtcars, family = binomial())
 
   performance::r2(model)
   dominance_analysis(model)
+
+  # Dominance Analysis with Weighted Logit Regression
+
+  model_wt <- glm(vs ~ cyl + carb + mpg, data = mtcars,
+    weights = wt, family = binomial())
+
+ dominance_analysis(model_wt, quote_args = "weights")
+
 }
 }
 \references{

From 5d85481ec0d2c14be51c599c5a3bf7f2f4996d8f Mon Sep 17 00:00:00 2001
From: Joseph Luchman <jluchman@gmail.com>
Date: Sat, 25 Jun 2022 10:56:47 -0500
Subject: [PATCH 3/3] stylistic updates to `dominance_analysis`

---
 DESCRIPTION                              |  7 +-
 R/dominance_analysis.R                   | 88 +++++++++++++++++-------
 man/dominance_analysis.Rd                | 21 +++---
 tests/testthat/test-dominance_analysis.R | 12 ++--
 4 files changed, 87 insertions(+), 41 deletions(-)

diff --git a/DESCRIPTION b/DESCRIPTION
index d1e92ec14..2b17a1f2e 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -58,7 +58,12 @@ Authors@R:
              family = "Morrison",
              role = "ctb",
              email = "dmorrison01@ucla.edu",
-             comment = c(ORCID = "0000-0002-7195-830X", Twitter = "@demstats1")))           
+             comment = c(ORCID = "0000-0002-7195-830X", Twitter = "@demstats1")),  
+      person(given = "Joseph",
+             family = "Luchman",
+             role = "ctb",
+             email = "jluchman@gmail.com",
+             comment = c(ORCID = "0000-0002-8886-9717")))
 Maintainer: Daniel Lüdecke <d.luedecke@uke.de>
 Description: Utilities for processing the parameters of various
     statistical models. Beyond computing p values, CIs, and other indices
diff --git a/R/dominance_analysis.R b/R/dominance_analysis.R
index 4630c3aa9..c467cadbc 100644
--- a/R/dominance_analysis.R
+++ b/R/dominance_analysis.R
@@ -35,25 +35,25 @@
 #' An object of class `"parameters_da"` is a list of `data.frame`s composed
 #' of the following elements:
 #' \describe{
-#'  \item{`general`}{A `data.frame` which associates dominance statistics with
+#'  \item{`General`}{A `data.frame` which associates dominance statistics with
 #'  model parameters. The variables in this `data.frame` include:
 #'   \describe{
-#'     \item{`parameter`}{Parameter names.}
-#'      \item{`general_dominance`}{Vector of general dominance statistics.
+#'     \item{`Parameter`}{Parameter names.}
+#'      \item{`General_Dominance`}{Vector of general dominance statistics.
 #'      The R2 ascribed to variables in the `all` argument are also reported
 #'      here though they are not general dominance statistics.}
-#'      \item{`standardized`}{Vector of general dominance statistics normalized
+#'      \item{`Percent`}{Vector of general dominance statistics normalized
 #'      to sum to 1.}
-#'      \item{`ranks`}{Vector of ranks applied to the general dominance
+#'      \item{`Ranks`}{Vector of ranks applied to the general dominance
 #'      statistics.}
-#'      \item{`subset`}{Names of the subset to which the parameter belongs in
+#'      \item{`Subset`}{Names of the subset to which the parameter belongs in
 #'      the dominance analysis.  Each other `data.frame` returned will refer
 #'      to these subset names.}}}
-#'  \item{`conditional_dominance`}{A `data.frame` of conditional dominance
+#'  \item{`Conditional`}{A `data.frame` of conditional dominance
 #'  statistics.  Each observation represents a subset and each variable
 #'  represents an the average increment to R2 with a specific number of
 #'  subsets in the model.  `NULL` if `conditional` argument is `FALSE`.}
-#'  \item{`complete_dominance`}{A `data.frame` of complete dominance
+#'  \item{`Complete`}{A `data.frame` of complete dominance
 #'  designations. The subsets in the observations are compared to the
 #'  subsets referenced in each variable. Whether the subset
 #'  in each variable dominates the subset in each observation is
@@ -339,12 +339,12 @@ dominance_analysis <- function(model, sets = NULL, all = NULL,
   }
 
   # Internal wrapper to ensure r2 values conform to domin ----
-  r2_wrap <- function(model, ...) {
+  .r2_wrap <- function(model, ...) {
     list(fitstat = performance::r2(model, ...)[[1]])
   }
 
   # Finalize and implement DA
-  args2domin <- append(list(formula_overall = fml, reg = reg, fitstat = list(r2_wrap, "fitstat"),
+  args2domin <- append(list(formula_overall = fml, reg = reg, fitstat = list(.r2_wrap, "fitstat"),
                     data = data, conditional = conditional, complete = complete,
                     sets = sets_processed, all = all_processed), args)
 
@@ -357,14 +357,16 @@ dominance_analysis <- function(model, sets = NULL, all = NULL,
       c(names(domir_res$General_Dominance)[1:(length(domir_res$General_Dominance) - length(set_names))],
         set_names)
 
-    if (conditional)
+    if (conditional) {
       rownames(domir_res$Conditional_Dominance) <- names(domir_res$General_Dominance)
 
+    }
+
   }
 
   if (complete) {
 
-    colnames(domir_res$Complete_Dominance) <- paste0("< ", names(domir_res$General_Dominance))
+    colnames(domir_res$Complete_Dominance) <- paste0("dmn_", names(domir_res$General_Dominance))
 
     dimnames(domir_res$Complete_Dominance) <- list(
       colnames(domir_res$Complete_Dominance),
@@ -441,11 +443,11 @@ dominance_analysis <- function(model, sets = NULL, all = NULL,
   if (conditional) {
 
     da_df_cdl <-
-      data.frame(subset = names(domir_res$General_Dominance))
+      data.frame(Subset = names(domir_res$General_Dominance))
 
     da_df_cdl <-
       datawizard::data_merge(da_df_cdl,
-                             data.frame(subset = names(domir_res$General_Dominance),
+                             data.frame(Subset = names(domir_res$General_Dominance),
                                         domir_res$Conditional_Dominance))
 
     da_df_cdl <-
@@ -459,11 +461,11 @@ dominance_analysis <- function(model, sets = NULL, all = NULL,
   if (complete) {
 
   da_df_cpt <-
-    data.frame(subset = names(domir_res$General_Dominance))
+    data.frame(Subset = names(domir_res$General_Dominance))
 
   da_df_cpt <-
     datawizard::data_merge(da_df_cpt,
-                           data.frame(subset = names(domir_res$General_Dominance),
+                           data.frame(Subset = names(domir_res$General_Dominance),
                                       domir_res$Complete_Dominance))
 
   da_df_cpt <-
@@ -475,15 +477,20 @@ dominance_analysis <- function(model, sets = NULL, all = NULL,
 
   else da_df_cpt <- NULL
 
-  da_list <- list(general = da_df_res,
-                  conditional = da_df_cdl,
-                  complete = da_df_cpt)
+  da_df_res <-
+    datawizard::data_rename(da_df_res,
+                            replacement = c("Parameter", "General_Dominance",
+                                            "Percent", "Ranks", "Subset"))
+
+  da_list <- list(General = da_df_res,
+                  Conditional = da_df_cdl,
+                  Complete = da_df_cpt)
 
   # add attributes and class
   attr(da_list, "model_R2") <- domir_res$Fit_Statistic_Overall
-  attr(da_list$general, "table_title") <- "General Dominance Statistics"
-  if (conditional) attr(da_list$conditional, "table_title") <- "Conditional Dominance Statistics"
-  if (complete) attr(da_list$complete, "table_title") <- "Complete Dominance Designations"
+  attr(da_list$General, "table_title") <- "General Dominance Statistics"
+  if (conditional) attr(da_list$Conditional, "table_title") <- "Conditional Dominance Statistics"
+  if (complete) attr(da_list$Complete, "table_title") <- "Complete Dominance Designations"
 
   class(da_list) <- c("parameters_da")
 
@@ -504,7 +511,42 @@ print.parameters_da <- function(x, digits = 3, ...) {
 
   cat("Model R2 Value: ", sprintf("%.*f", digits, attr(x, "model_R2")), "\n\n")
 
-  cat(insight::export_table(x, digits = digits, ...))
+  printed_x <- x
+
+  printed_x$General <- datawizard::data_rename(x$General,
+                                               pattern = "General_Dominance",
+                                               replacement = "General Dominance")
+
+  if (!is.null(x$Conditional)) {
+
+    cdl_col <- ncol(x$Conditional)
+
+    cdl_names<- paste0("IVs_", 1:(cdl_col - 1))
+
+    cdl_names_rep <- paste("IVs:", 1:(cdl_col - 1))
+
+    printed_x$Conditional <-
+      datawizard::data_rename(x$Conditional,
+                  pattern = cdl_names,
+                  replacement = cdl_names_rep)
+
+  }
+
+  if (!is.null(x$Complete)) {
+
+    cpt_names <- names(x$Complete)[-1]
+
+    cpt_names_rep <- gsub("dmn_", "< ",
+                          cpt_names)
+
+    printed_x$Complete <-
+      datawizard::data_rename(x$Complete,
+                              pattern = cpt_names,
+                              replacement = cpt_names_rep)
+
+  }
+
+  cat(insight::export_table(printed_x, digits = digits, ...))
 
   invisible(x)
 
diff --git a/man/dominance_analysis.Rd b/man/dominance_analysis.Rd
index 9960d0b52..2d9272f16 100644
--- a/man/dominance_analysis.Rd
+++ b/man/dominance_analysis.Rd
@@ -55,25 +55,25 @@ Object of class \code{"parameters_da"}.
 An object of class \code{"parameters_da"} is a list of \code{data.frame}s composed
 of the following elements:
 \describe{
-\item{\code{general}}{A \code{data.frame} which associates dominance statistics with
+\item{\code{General}}{A \code{data.frame} which associates dominance statistics with
 model parameters. The variables in this \code{data.frame} include:
 \describe{
-\item{\code{parameter}}{Parameter names.}
-\item{\code{general_dominance}}{Vector of general dominance statistics.
+\item{\code{Parameter}}{Parameter names.}
+\item{\code{General_Dominance}}{Vector of general dominance statistics.
 The R2 ascribed to variables in the \code{all} argument are also reported
 here though they are not general dominance statistics.}
-\item{\code{standardized}}{Vector of general dominance statistics normalized
+\item{\code{Percent}}{Vector of general dominance statistics normalized
 to sum to 1.}
-\item{\code{ranks}}{Vector of ranks applied to the general dominance
+\item{\code{Ranks}}{Vector of ranks applied to the general dominance
 statistics.}
-\item{\code{subset}}{Names of the subset to which the parameter belongs in
-the dominance analysis.  Each other \code{data.frame} will refer to these
-subset names.}}}
-\item{\code{conditional_dominance}}{A \code{data.frame} of conditional dominance
+\item{\code{Subset}}{Names of the subset to which the parameter belongs in
+the dominance analysis.  Each other \code{data.frame} returned will refer
+to these subset names.}}}
+\item{\code{Conditional}}{A \code{data.frame} of conditional dominance
 statistics.  Each observation represents a subset and each variable
 represents an the average increment to R2 with a specific number of
 subsets in the model.  \code{NULL} if \code{conditional} argument is \code{FALSE}.}
-\item{\code{complete_dominance}}{A \code{data.frame} of complete dominance
+\item{\code{Complete}}{A \code{data.frame} of complete dominance
 designations. The subsets in the observations are compared to the
 subsets referenced in each variable. Whether the subset
 in each variable dominates the subset in each observation is
@@ -131,7 +131,6 @@ require("performance")) {
   dominance_analysis(model)
 
   # Dominance Analysis with Weighted Logit Regression
-
   model_wt <- glm(vs ~ cyl + carb + mpg, data = mtcars,
     weights = wt, family = binomial())
 
diff --git a/tests/testthat/test-dominance_analysis.R b/tests/testthat/test-dominance_analysis.R
index d9396ccbe..46fe8230d 100644
--- a/tests/testthat/test-dominance_analysis.R
+++ b/tests/testthat/test-dominance_analysis.R
@@ -14,7 +14,7 @@ if (requiet("testthat") && requiet("performance") && requiet("domir") &&
     gnrl_domir <- c(NA, DA_domir$General_Dominance)
     names(gnrl_domir) <- NULL
 
-    gnrl_da <- DA_performance$general$general_dominance
+    gnrl_da <- DA_performance$General$General_Dominance
 
     expect_equal(gnrl_domir,
                  gnrl_da)
@@ -25,7 +25,7 @@ if (requiet("testthat") && requiet("performance") && requiet("domir") &&
     cdl_domir <- DA_domir$Conditional_Dominance
     dimnames(cdl_domir) <-c(NULL, NULL)
 
-    cdl_da <- as.matrix(DA_performance$conditional[,-1])
+    cdl_da <- as.matrix(DA_performance$Conditional[,-1])
     dimnames(cdl_da) <-c(NULL, NULL)
 
     expect_equal(cdl_domir,
@@ -37,7 +37,7 @@ if (requiet("testthat") && requiet("performance") && requiet("domir") &&
     cpt_domir <- DA_domir$Complete_Dominance
     dimnames(cpt_domir) <- list(NULL, NULL)
 
-    cpt_da <- t(DA_performance$complete[,-1])
+    cpt_da <- t(DA_performance$Complete[,-1])
     dimnames(cpt_da) <- list(NULL, NULL)
 
     expect_equal(cpt_domir,
@@ -58,13 +58,13 @@ if (requiet("testthat") && requiet("performance") && requiet("domir") &&
     names(domir_all_sub_r2) <-NULL
 
     expect_equal(domir_all_sub_r2,
-                 with(DA_performance2$general, general_dominance[subset == "all"]))
+                 with(DA_performance2$General, General_Dominance[Subset == "all"]))
 
     gnrl_domir2 <- DA_domir2$General_Dominance
     names(gnrl_domir2) <- NULL
 
-    gnrl_da2 <- aggregate(DA_performance2$general$general_dominance,
-                          list(DA_performance2$general$subset), mean)
+    gnrl_da2 <- aggregate(DA_performance2$General$General_Dominance,
+                          list(DA_performance2$General$Subset), mean)
 
     gnrl_da2 <- gnrl_da2[which(gnrl_da2$Group.1 %in% c("cyl", "set1")),]