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Inhouse-processing of parameter-tidying (#447)
* Inhouse-processing of parameter-tidying * no nested if-sztatement * Update DESCRIPTION * Update DESCRIPTION * Update ordinal.md * Update test-estimate_grouplevel.R * Update DESCRIPTION
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‎DESCRIPTION

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@@ -1,7 +1,7 @@
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Type: Package
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Package: modelbased
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Title: Estimation of Model-Based Predictions, Contrasts and Means
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Version: 0.10.0.2
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Version: 0.10.0.3
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Authors@R:
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c(person(given = "Dominique",
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family = "Makowski",
@@ -102,3 +102,4 @@ Roxygen: list(markdown = TRUE)
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Config/Needs/check: stan-dev/cmdstanr
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Config/Needs/website: easystats/easystatstemplate
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LazyData: true
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Remotes: easystats/bayestestR, easystats/parameters

‎R/format.R

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@@ -498,31 +498,19 @@ format.marginaleffects_contrasts <- function(x, model = NULL, p_adjust = NULL, c
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# coefficient column is named, because we replace that column name with an
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# appropriate name of the predictions (e.g. "Difference", "Probability" or
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# "Mean")
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if (is.null(attributes(x)$posterior_draws)) {
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# frequentist
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params <- suppressWarnings(parameters::model_parameters(x, ci = ci, verbose = FALSE))
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coefficient_name <- intersect(
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c(attributes(params)$coefficient_name, "Coefficient", "Slope", "Predicted"),
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colnames(params)
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)[1]
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} else {
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# Bayesian
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params <- suppressWarnings(bayestestR::describe_posterior(x, ci = ci, verbose = FALSE, ...))
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## FIXME: needs to be fixed in bayestestR: categorical models don't return group column
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# see https://github.com/easystats/bayestestR/issues/692
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if (info$is_categorical) {
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params$group <- .safe(x$group)
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}
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coefficient_name <- intersect(
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c(attributes(params)$coefficient_name, "Median", "Mean", "MAP"),
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colnames(params)
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)[1]
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# we need to remove some more columns
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remove_columns <- c(remove_columns, "rowid")
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# and modify the estimate name - if it's not a dpar
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if (!is.null(estimate_name) && !tolower(estimate_name) %in% .brms_aux_elements()) {
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estimate_name <- coefficient_name
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}
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params <- suppressWarnings(parameters::model_parameters(x, ci = ci, verbose = FALSE, ...))
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# the different functions and models (Bayesian, frequentist) have different
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# column names for their "coefficient". We now extract the relevant one.
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possible_colnames <- c(
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attributes(params)$coefficient_name,
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"Coefficient", "Slope", "Predicted", "Median", "Mean", "MAP"
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)
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coefficient_name <- intersect(possible_colnames, colnames(params))[1]
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# we need to remove some more columns
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remove_columns <- c(remove_columns, "rowid")
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# and modify the estimate name - if it's not a dpar
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if (!is.null(attributes(x)$posterior_draws) && !is.null(estimate_name) && !tolower(estimate_name) %in% .brms_aux_elements()) { # nolint
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estimate_name <- coefficient_name
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}
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# rename the "term" and "hypothesis" column (which we get from contrasts)
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colnames(params)[colnames(params) == "term"] <- "Parameter"

‎tests/testthat/_snaps/windows/ordinal.md

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@@ -49,38 +49,38 @@
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Output
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Estimated Marginal Means
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Sepal.Width | Response | Median | 95% CI | pd | ROPE | % in ROPE
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Sepal.Width | Response | Median | 95% CI | pd | ROPE | % in ROPE
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-----------------------------------------------------------------------------------
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2.00 | setosa | 0.00 | [0.00, 0.01] | 100% | [-0.10, 0.10] | 100%
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2.00 | versicolor | 0.86 | [0.65, 0.95] | 100% | [-0.10, 0.10] | 0%
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2.00 | virginica | 0.14 | [0.05, 0.34] | 100% | [-0.10, 0.10] | 28.00%
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2.27 | setosa | 0.00 | [0.00, 0.02] | 100% | [-0.10, 0.10] | 100%
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2.27 | versicolor | 0.78 | [0.60, 0.90] | 100% | [-0.10, 0.10] | 0%
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2.27 | virginica | 0.21 | [0.10, 0.40] | 100% | [-0.10, 0.10] | 0%
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2.53 | setosa | 0.02 | [0.01, 0.06] | 100% | [-0.10, 0.10] | 100%
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2.53 | versicolor | 0.66 | [0.52, 0.78] | 100% | [-0.10, 0.10] | 0%
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2.53 | virginica | 0.32 | [0.20, 0.45] | 100% | [-0.10, 0.10] | 0%
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2.80 | setosa | 0.09 | [0.04, 0.16] | 100% | [-0.10, 0.10] | 65.72%
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2.80 | versicolor | 0.49 | [0.39, 0.59] | 100% | [-0.10, 0.10] | 0%
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2.80 | virginica | 0.41 | [0.32, 0.52] | 100% | [-0.10, 0.10] | 0%
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3.07 | setosa | 0.27 | [0.19, 0.36] | 100% | [-0.10, 0.10] | 0%
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3.07 | versicolor | 0.30 | [0.21, 0.39] | 100% | [-0.10, 0.10] | 0%
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3.07 | virginica | 0.43 | [0.33, 0.53] | 100% | [-0.10, 0.10] | 0%
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3.33 | setosa | 0.57 | [0.47, 0.68] | 100% | [-0.10, 0.10] | 0%
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3.33 | versicolor | 0.12 | [0.06, 0.21] | 100% | [-0.10, 0.10] | 29.76%
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3.33 | virginica | 0.30 | [0.20, 0.40] | 100% | [-0.10, 0.10] | 0%
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3.60 | setosa | 0.82 | [0.68, 0.91] | 100% | [-0.10, 0.10] | 0%
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3.60 | versicolor | 0.03 | [0.01, 0.08] | 100% | [-0.10, 0.10] | 100%
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3.60 | virginica | 0.14 | [0.07, 0.26] | 100% | [-0.10, 0.10] | 17.37%
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3.87 | setosa | 0.94 | [0.83, 0.98] | 100% | [-0.10, 0.10] | 0%
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3.87 | versicolor | 0.01 | [0.00, 0.03] | 100% | [-0.10, 0.10] | 100%
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3.87 | virginica | 0.05 | [0.02, 0.15] | 100% | [-0.10, 0.10] | 89.59%
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4.13 | setosa | 0.98 | [0.91, 1.00] | 100% | [-0.10, 0.10] | 0%
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4.13 | versicolor | 0.00 | [0.00, 0.01] | 100% | [-0.10, 0.10] | 100%
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4.13 | virginica | 0.02 | [0.00, 0.08] | 100% | [-0.10, 0.10] | 100%
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4.40 | setosa | 0.99 | [0.95, 1.00] | 100% | [-0.10, 0.10] | 0%
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4.40 | versicolor | 0.00 | [0.00, 0.00] | 100% | [-0.10, 0.10] | 100%
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4.40 | virginica | 0.01 | [0.00, 0.04] | 100% | [-0.10, 0.10] | 100%
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2.00 | setosa | 0.00 | [0.00, 0.01] | 100% | [-0.10, 0.10] | 100%
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2.00 | versicolor | 0.86 | [0.65, 0.95] | 100% | [-0.10, 0.10] | 0%
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2.00 | virginica | 0.14 | [0.05, 0.34] | 100% | [-0.10, 0.10] | 28.00%
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2.27 | setosa | 0.00 | [0.00, 0.02] | 100% | [-0.10, 0.10] | 100%
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2.27 | versicolor | 0.78 | [0.60, 0.90] | 100% | [-0.10, 0.10] | 0%
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2.27 | virginica | 0.21 | [0.10, 0.40] | 100% | [-0.10, 0.10] | 0%
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2.53 | setosa | 0.02 | [0.01, 0.06] | 100% | [-0.10, 0.10] | 100%
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2.53 | versicolor | 0.66 | [0.52, 0.78] | 100% | [-0.10, 0.10] | 0%
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2.53 | virginica | 0.32 | [0.20, 0.45] | 100% | [-0.10, 0.10] | 0%
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2.80 | setosa | 0.09 | [0.04, 0.16] | 100% | [-0.10, 0.10] | 65.72%
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2.80 | versicolor | 0.49 | [0.39, 0.59] | 100% | [-0.10, 0.10] | 0%
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2.80 | virginica | 0.41 | [0.32, 0.52] | 100% | [-0.10, 0.10] | 0%
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3.07 | setosa | 0.27 | [0.19, 0.36] | 100% | [-0.10, 0.10] | 0%
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3.07 | versicolor | 0.30 | [0.21, 0.39] | 100% | [-0.10, 0.10] | 0%
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3.07 | virginica | 0.43 | [0.33, 0.53] | 100% | [-0.10, 0.10] | 0%
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3.33 | setosa | 0.57 | [0.47, 0.68] | 100% | [-0.10, 0.10] | 0%
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3.33 | versicolor | 0.12 | [0.06, 0.21] | 100% | [-0.10, 0.10] | 29.76%
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3.33 | virginica | 0.30 | [0.20, 0.40] | 100% | [-0.10, 0.10] | 0%
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3.60 | setosa | 0.82 | [0.68, 0.91] | 100% | [-0.10, 0.10] | 0%
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3.60 | versicolor | 0.03 | [0.01, 0.08] | 100% | [-0.10, 0.10] | 100%
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3.60 | virginica | 0.14 | [0.07, 0.26] | 100% | [-0.10, 0.10] | 17.37%
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3.87 | setosa | 0.94 | [0.83, 0.98] | 100% | [-0.10, 0.10] | 0%
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3.87 | versicolor | 0.01 | [0.00, 0.03] | 100% | [-0.10, 0.10] | 100%
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3.87 | virginica | 0.05 | [0.02, 0.15] | 100% | [-0.10, 0.10] | 89.59%
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4.13 | setosa | 0.98 | [0.91, 1.00] | 100% | [-0.10, 0.10] | 0%
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4.13 | versicolor | 0.00 | [0.00, 0.01] | 100% | [-0.10, 0.10] | 100%
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4.13 | virginica | 0.02 | [0.00, 0.08] | 100% | [-0.10, 0.10] | 100%
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4.40 | setosa | 0.99 | [0.95, 1.00] | 100% | [-0.10, 0.10] | 0%
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4.40 | versicolor | 0.00 | [0.00, 0.00] | 100% | [-0.10, 0.10] | 100%
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4.40 | virginica | 0.01 | [0.00, 0.04] | 100% | [-0.10, 0.10] | 100%
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Variable predicted: Species
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Predictors modulated: Sepal.Width

‎tests/testthat/test-estimate_grouplevel.R

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@@ -129,11 +129,11 @@ test_that("estimate_grouplevel - Bayesian, rstanarm", {
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skip_if(is.null(m))
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out <- estimate_grouplevel(m)
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expect_identical(dim(out), c(4L, 8L))
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expect_identical(dim(out), c(3L, 8L))
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expect_named(out, c("Group", "Level", "Parameter", "Median", "MAD", "CI", "CI_low", "CI_high"))
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out <- estimate_grouplevel(m, dispersion = FALSE)
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expect_identical(dim(out), c(4L, 7L))
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expect_identical(dim(out), c(3L, 7L))
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out <- estimate_grouplevel(m, type = "total", dispersion = FALSE)
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expect_identical(dim(out), c(3L, 4L))

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