Package: qcaERT 0.1.0

Breno A. H. Marisguia

qcaERT: Enhanced Robustness Tests for Qualitative Comparative Analysis

Provides functions for assessing and visualizing robustness in Qualitative Comparative Analysis (QCA) workflows built with the 'QCA' package, including calibration thresholds, inclusion cutoffs, frequency cutoffs, case influence, subsample stability, alternative analysis settings, theory-specific condition sets, cluster-specific patterns, and solution summaries. Methods build on Dusa (2019) <doi:10.1007/978-3-319-75668-4> and Ragin (2014, ISBN:9780520280038).

Authors:Breno A. H. Marisguia [aut, cre, cph]

qcaERT_0.1.0.tar.gz
qcaERT_0.1.0.tar.gz(r-4.7-any)qcaERT_0.1.0.tar.gz(r-4.6-any)
qcaERT_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
qcaERT/json (API)
NEWS

# Install 'qcaERT' in R:
install.packages('qcaERT', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.18 score 1 scripts 10 exports 4 dependencies

Last updated from:22b1d7f0d2. Checks:4 OK. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK261
source / vignettesOK184
linux-release-x86_64OK225
wasm-releaseOK121

Exports:altset.testcalib.testcluster.testincl.testloo.testncut.testsol.chartsol.dfsubsample.testtheory.test

Dependencies:admiscdeclaredQCAvenn

Calibration robustness and alternative sets

Rendered fromqcaERT-calibration.Rmdusingknitr::rmarkdownon May 27 2026.

Last update: 2026-05-27
Started: 2026-05-27

Getting started with qcaERT

Rendered fromqcaERT-overview.Rmdusingknitr::rmarkdownon May 27 2026.

Last update: 2026-05-27
Started: 2026-05-27

Reading qcaERT result objects

Rendered fromqcaERT-result-objects.Rmdusingknitr::rmarkdownon May 27 2026.

Last update: 2026-05-27
Started: 2026-05-27

Readme and manuals

Help Manual

Help pageTopics
qcaERT: Enhanced robustness tests for QCAqcaERT-package qcaERT
Alternative-set robustness test for QCA solutionsaltset.test as.data.frame.altset_test print.altset_test
Calibration-threshold robustness test for QCA solutionsas.data.frame.calib_test calib.test print.calib_test
Cluster heterogeneity diagnostics for QCA configurationsas.data.frame.cluster_test cluster.test print.cluster_test
Inclusion-cutoff robustness test for QCA solutionsas.data.frame.incl_test incl.test print.incl_test
Leave-one-out robustness test for QCA solutionsas.data.frame.loo_test loo.test print.loo_test
Truth table frequency-cutoff robustness test for QCA solutionsas.data.frame.ncut_test ncut.test print.ncut_test
qcaERT argument and output conventionsqcaERT_conventions
Plot and chart qcaERT resultsplot.calib_test plot.incl_test plot.theory_test qcaERT_plots
Choose a qcaERT robustness toolqcaERT_tests
Draw a chart from a sol.df tablesol.chart
Build a compact solution table from QCA minimization outputsol.df
Subsample robustness test for QCA solutionsas.data.frame.subsample_test print.subsample_test subsample.test
Theory-specification robustness for QCA modelsas.data.frame.theory_test print.theory_test theory.test