incl.test() and ncut.test() now leave first_failing missing when the
next proposed cutoff lies outside the admissible search range, because that
value was not analyzed. Inclusion-cutoff trace plots likewise omit untested
boundary proposals and their reference lines.ncut.test() now rejects a baseline n.cut greater than the number of rows
in the analysis data.altset.test() now verifies that every tested condition or outcome
membership in calib.data matches the reference calibration reconstructed
from raw.data and calib_spec.n_fit_deltas = 0 identifies a
completed comparison with no differences beyond fit_tol, whereas NA
identifies a draw in which fit was not compared. Printed summaries now show
the separate denominators for draw availability, formula preservation, and
fit preservation.necessity argument from cluster.test(). The function
now documents its scope explicitly as the sufficiency assessment of selected
solution formulas and prime implicants, and its displayed configuration
values no longer include a redundant solution-type prefix.cluster.test() pooled, cluster-specific, and within-unit
calculations. Missing unit identifiers no longer remove rows from pooled or
cluster fit, and duplicate unit-cluster observations are rejected.sample_prop rounding is unchanged.R (>= 3.5.0), matching the serialization format used by the shipped
demonstration data.whr_raw, whr_calibrated, and whr_calib_spec.plot(..., type = "trace") no longer duplicates an evaluated failing threshold.This is the first public version of qcaERT.
calib.test() for calibration-threshold robustness.incl.test() for inclusion-cutoff robustness.ncut.test() for frequency-cutoff robustness.loo.test() for leave-one-out case influence.subsample.test() for repeated subsample stability.altset.test() for sampled alternative analysis settings.theory.test() for comparing theoretically motivated condition-set
specifications.cluster.test() for cluster, group, and repeated-unit heterogeneity.sol.df() for compact QCA solution tables.sol.chart() for visual presentation of sol.df() tables.solution, include, dir.exp, which_M, and i_mode.exclude_mode, exclude_recompute, and exclude_static.diagnostics for detailed/internal results.results for the clean table.settings for the analysis settings.baseline, bounds, by_direction,
by_case, by_run, by_draw, and summary where relevant.print() methods to show concise summaries.as.data.frame() methods to return the clean table.cluster.test() returns results$overview, results$clusters, and
results$units; as.data.frame() returns results$overview.theory.test() returns results$models, results$solutions, and
results$pairwise; as.data.frame() returns results$models.