Package: cases 0.2.0

Max Westphal

cases: Stratified Evaluation of Subgroup Classification Accuracy

Enables simultaneous statistical inference for the accuracy of multiple classifiers in multiple subgroups (strata). For instance, allows to perform multiple comparisons in diagnostic accuracy studies with co-primary endpoints sensitivity and specificity (Westphal M, Zapf A. Statistical inference for diagnostic test accuracy studies with multiple comparisons. Statistical Methods in Medical Research. 2024;0(0). <doi:10.1177/09622802241236933>).

Authors:Max Westphal [aut, cre]

cases_0.2.0.tar.gz
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cases_0.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
cases/json (API)
NEWS

# Install 'cases' in R:

install.packages('cases', repos = c('https://maxwestphal.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/maxwestphal/cases/issues

Pkgdown/docs site:https://maxwestphal.github.io

Datasets:

data_wdbc - Breast Cancer Wisconsin (Diagnostic) Data Set

On CRAN:

4.51 score 2 stars 16 scripts 190 downloads 13 exports 53 dependencies

Last updated from:4eb54811e3. Checks:9 OK. Indexed: yes.

Target	Result	Time
linux-devel-x86_64	OK	206
source / vignettes	OK	222
linux-release-x86_64	OK	205
macos-release-arm64	OK	166
macos-oldrel-arm64	OK	259
windows-devel	OK	139
windows-release	OK	155
windows-oldrel	OK	142
wasm-release	OK	124

Exports:%>%categorize compare define_contrast draw_data draw_data_lfc draw_data_prb draw_data_roc evaluate generate_instance_lfc generate_instance_roc process_instance visualize

Dependencies:ADGofTest bindata boot class cli cluster codetools colorspace copula corrplot cpp11 dplyr e1071 extraDistr farver generics ggplot2 glue gsl gtable isoband labeling lattice lifecycle magrittr MASS Matrix multcomp mvtnorm numDeriv pcaPP pillar pkgconfig proxy pspline R6 RColorBrewer Rcpp RcppArmadillo rlang S7 sandwich scales stabledist survival TH.data tibble tidyselect utf8 vctrs viridisLite withr zoo

R package cases: overview

Rendered frompackage_overview.Rmdusingknitr::rmarkdownon May 13 2026.

Last update: 2024-07-17
Started: 2022-08-06

Real-world example: biomarker assessment and prediction model evaluation

Rendered fromexample_wdbc.Rmdusingknitr::rmarkdownon May 13 2026.

Last update: 2025-01-04
Started: 2022-08-06

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
'cases' package	cases-package cases
Categorize continuous values	categorize
Compare predictions and labels	compare
Create an AR(1) correlation matrix	cormat_ar1
Create an equicorrelation matrix	cormat_equi
Breast Cancer Wisconsin (Diagnostic) Data Set	data_wdbc
Define a contrast (matrix) to specify exact hypothesis system	define_contrast
Generate binary data	draw_data
Generate binary data (LFC model)	draw_data_lfc
Sample binary data (single sample)	draw_data_prb
Generate binary data (ROC model)	draw_data_roc
Evaluate the accuracy of multiple (candidate) classifiers in several subgroups	evaluate
Generate data sets under least favorable parameter configurations	generate_instance_lfc
Generate data sets under realistic parameter configurations	generate_instance_roc
Analyze simulated synthetic datasets.	process_instance
Visualize evaluation results	visualize