From 0fb2a8d944e16184f2999e83c9635b14e42d1d97 Mon Sep 17 00:00:00 2001 From: Koen Derks Date: Mon, 9 Dec 2024 13:16:11 +0100 Subject: [PATCH] Update npvp name --- DESCRIPTION | 2 +- tests/testthat/test-fairness-selection.R | 2 +- vignettes/articles/model-fairness.Rmd | 2 +- 3 files changed, 3 insertions(+), 3 deletions(-) diff --git a/DESCRIPTION b/DESCRIPTION index 8f1645b7..0edd2681 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,7 +1,7 @@ Package: jfa Title: Statistical Methods for Auditing Version: 0.7.3 -Date: 2024-12-02 +Date: 2024-12-09 Authors@R: c( person("Koen", "Derks", email = "k.derks@nyenrode.nl", role = c("aut", "cre"), comment = c(ORCID = '0000-0002-5533-9349')), diff --git a/tests/testthat/test-fairness-selection.R b/tests/testthat/test-fairness-selection.R index bcbaa725..646e863e 100644 --- a/tests/testthat/test-fairness-selection.R +++ b/tests/testthat/test-fairness-selection.R @@ -32,7 +32,7 @@ test_that(desc = "Validation of fairness selection", { # Accuracy parity outcome <- fairness_selection(q1 = 1, q2 = 1, q3 = 3) expect_equal(outcome$measure, "ap") - # Negative predictive rate parity + # Negative predictive value parity outcome <- fairness_selection(q1 = 1, q2 = 1, q3 = 2, q4 = 2) expect_equal(outcome$measure, "npvp") # Specificity parity diff --git a/vignettes/articles/model-fairness.Rmd b/vignettes/articles/model-fairness.Rmd index d92094e5..2922f33c 100644 --- a/vignettes/articles/model-fairness.Rmd +++ b/vignettes/articles/model-fairness.Rmd @@ -473,7 +473,7 @@ tailored to a specific context and dataset by answering the questions in the developed decision-making workflow. The fairness measure that can be selected include disparate impact, equalized odds, false positive rate parity, false negative rate parity, predictive rate parity, equal opportunity, specificity -parity, negative predictive rate parity, accuracy parity [@castelnovo_2022; +parity, negative predictive value parity, accuracy parity [@castelnovo_2022; @feldman_2015; @friedler_2019; @hardt_2016, @verma_2018]. After answering the questions in the decision-making workflow and selecting the fairness measure to apply, a graphical representation of the followed path can be created based