Package: qcaERT 0.1.2

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_0.1.2.tar.gz
qcaERT_0.1.2.zip(r-4.7-any)qcaERT_0.1.2.zip(r-4.6-any)qcaERT_0.1.2.zip(r-4.5-any)
qcaERT_0.1.2.tgz(r-4.6-any)qcaERT_0.1.2.tgz(r-4.5-any)
qcaERT_0.1.2.tar.gz(r-4.7-any)qcaERT_0.1.2.tar.gz(r-4.6-any)
qcaERT_0.1.2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
qcaERT/json (API)

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

Bug tracker:https://github.com/marisguia/qcaert/issues

Datasets:
  • whr_calib_spec - Calibration specifications for the WHR demonstration data
  • whr_calibrated - Calibrated World Happiness Report 2025 demonstration data
  • whr_raw - World Happiness Report 2025 demonstration data

On CRAN:

Conda:

4.88 score 1 stars 195 downloads 10 exports 4 dependencies

Last updated from:33654ba6e5. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develOK187
source / vignettesOK193
linux-releaseOK230
macos-releaseOK369
macos-oldrelOK280
windows-develOK261
windows-releaseOK219
windows-oldrelOK203
wasm-releaseOK87

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

Dependencies:admiscdeclaredQCAvenn

Calibration robustness and alternative sets
Use calibration specifications | Conditions and test.conditions | Outcome calibration | Anchors by calibration type | Scale-aware perturbations | Direct, indirect, and six-threshold calibration | From calibration bounds to alternative sets | Plotting calibration results
Rendered fromqcaERT-calibration.Rmdusingknitr::rmarkdown

Last update: 2026-07-29
Started: 2026-05-23

Getting started with qcaERT
Start from a QCA analysis | Choose a robustness test | Test inclusion and frequency cutoffs | Test calibration thresholds | Test cases and samples | Test alternative analysis sets | Compare theory specifications | Test clusters | Plot selected results | Next
Rendered fromqcaERT-overview.Rmdusingknitr::rmarkdown

Last update: 2026-07-29
Started: 2026-05-23

Reading qcaERT result objects
Boundary tests | Case and sample tests | Alternative-set tests | Cluster tests | Theory tests | Solution tables | What to inspect first
Rendered fromqcaERT-result-objects.Rmdusingknitr::rmarkdown

Last update: 2026-07-29
Started: 2026-05-23

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 solutionsas.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
Calibration specifications for the WHR demonstration datawhr_calib_spec
Calibrated World Happiness Report 2025 demonstration datawhr_calibrated
World Happiness Report 2025 demonstration datawhr_raw