contentvalidR 0.4.0

Fourth public release. v0.4.0 connects content validation to what comes after it: a documented handoff carries the items that survived content review, and the evidence behind each decision, into empirical scale development. It also adds a stricter, selectable criterion for parallel analysis, and fixes the two packaging problems that returned the 0.3.x CRAN submissions.

The package continues to declare Imports: stats only.

No default changes. Existing calls return the same values as in 0.3.1; qfactor_content() results gain two fields recording the parallel analysis criterion that ran.

New function: content_handoff().

Handoff to empirical validation

• Added content_handoff(), which packages a finished workflow’s item decisions for the next stage of scale development (#27). It carries the item names that survived content review, the construct each belongs to where the design defines one, a per-item evidence table with the decision rule that was applied, the statistics behind each decision, and the provenance of the analysis.
• The object shape is schema version 1, agreed with the nomologR package, which consumes it in nomo_screen() and nomo_run(). Every field is a base type, so neither package depends on the other.
• Items that do not meet keep stay in the evidence table with carried = FALSE rather than disappearing, and the printed output says plainly that surviving content review does not establish how an item will behave empirically.
• New vignette, From Content Validity to Empirical Validation, running from an expert panel through the handoff into an empirical workflow.

Selectable parallel analysis criterion

• qfactor_content() gains parallel_criterion, choosing what parallel analysis compares observed eigenvalues against (#26). "mean" stays the default, the rule Horn (1965) described and Zwick and Velicer (1986) evaluated. "percentile" compares against an upper percentile of the simulated eigenvalue distribution, following Glorfeld (1995), who found that Horn’s procedure still tends to retain one or two factors too many.
• The percentile level is selectable through percentile, defaulting to 95. Both criteria read the same simulation, so they are directly comparable from one seeded run, and the result records parallel_criterion and percentile alongside the comparison values in parallel_eigen.

Packaging

• .Rbuildignore now excludes .git, .gitignore, and .gitattributes. Building a release tarball from a git worktree checkout writes .git as a file rather than a directory, which R CMD build does not drop, and CRAN’s incoming pretest reported it as a hidden file included in error (#14).

contentvalidR 0.3.1

Patch release for the CRAN submission. Package code, documentation of methods, and results are unchanged from 0.3.0.

• README links to the license and the roadmap now use full URLs. The relative links pointed at files that are not part of the built package, which CRAN’s incoming checks report as invalid file URIs.

contentvalidR 0.3.0

Third public release, and the first prepared for CRAN. Every addition rests on published, verifiable methodology, and one design rule runs through the release: where more than one published method exists, researchers choose through an argument whose default is the best-supported option. Methods with published evidence against them stay available for reproducing earlier work, but they are never the default, and selecting one prints the critique.

The package continues to declare Imports: stats only.

Two defaults change results for existing code. qfactor_content() now chooses the number of factors by parallel analysis, and expert_validity() relevance mode now bootstraps an interval for panel agreement, so set seed when printed output must be reproducible. Other existing results are unchanged; the new interval and agreement columns are additions.

New function: panel_agreement().

Panel-level agreement for expert panels

• Added panel_agreement(), reporting one coefficient for how consistently an expert panel rated the whole item set, with a bootstrap interval. It complements the item-level I-CVI and modified kappa rather than replacing them.
• Krippendorff’s alpha is the default, computed from the coincidence matrix (Krippendorff, 2011) at a selectable measurement level: ordinal (the default), nominal, or interval. It reproduces the worked example in Krippendorff (2011) and agrees with irr::kripp.alpha().
• Gwet’s AC1 (Gwet, 2008) is available but is never the default, and selecting it prints the critique in Vach and Gerke (2023).
• Intervals resample items with all of their ratings, following Zapf et al. (2016), who found Krippendorff’s original bootstrap under-covered.
• expert_validity() relevance mode reports panel agreement in its scale summary, controlled by agreement, agreement_level, agreement_B, and seed.
• Output reports the share of identical rating pairs next to the coefficient, and explains that alpha can be low when ratings cluster on one value, so a low alpha on a close-agreeing panel is not read as a poor panel.

Evidence-based factor retention for qfactor_content()

• Behavior change: qfactor_content() now chooses the number of factors with Horn’s (1965) parallel analysis by default, instead of Kaiser’s eigenvalue-greater-than-1 rule. Calls that relied on the old default can return a different number of factors. Use retention = "kaiser" to reproduce earlier results; it prints the finding of Zwick and Velicer (1986) that the rule severely overestimates the number of components.
• Parallel analysis simulates random data with the same size and missing cells as the ratings. New n_iter and seed arguments control it, and the result records retention, k_suggested, and parallel_eigen.
• A supplied k_factors still takes precedence, and is recorded as retention = "fixed".
• qfactor_content() now cites Schriesheim et al. (1993, 1999), and signal_detection() cites Anderson and Gerbing (1991).

Packaging

• DESCRIPTION now gives DOIs for the methods it cites, and citation metadata is stamped for 0.3.0.
• agreement_summary() and the plot() methods for sort, rating, expert, and sort-power objects now have runnable examples, so every help page shows how to use its function. agreement_summary() also points to panel_agreement().

Selectable intervals for proportion indices

• cvi() now reports an interval for each I-CVI (I_CVI_low, I_CVI_high), and compute_psa() does the same for each Psa (psa_low, psa_high). Both indices previously appeared as bare proportions, usually from small panels.
• The interval method is selectable: ci in those two functions, and proportion_ci in expert_validity() and sort_validity(). The options are the Wilson score interval (the default; Wilson, 1927), which Newcombe (1998) recommends over the Wald interval; the Agresti-Coull adjusted Wald interval (Agresti & Coull, 1998); and the Clopper-Pearson exact interval (Clopper & Pearson, 1934), which is conservative. Printed output names the method, the interval level, and the method’s limits.
• The new interval columns have their own names, so they never collide with the Aiken’s V ci_low and ci_high columns in expert_validity().
• Point estimates are unchanged.

contentvalidR 0.2.0

Second public release. v0.1.0 established three item-level workflows; v0.2.0 adds the two questions those workflows could not answer — whether conclusions depend on the particular judges used, and whether the item set covers its intended domain — together with multi-round comparison, expert-panel planning, reporting helpers, and a substantial rework of how results explain themselves.

The package continues to declare Imports: stats only. Every method here is implemented in base R, so the package installs without a compiler toolchain.

New flagship workflows: judge_validity() and domain_validity(). New supporting functions: gtheory_content(), content_structure(), similarity_from_sort(), compare_rounds(), expert_power(), content_report(), contentvalid_glossary(), and an as.data.frame() method for workflow objects.

Multi-round comparison, planning, and reporting

• Added compare_rounds(), comparing two or more fitted workflow objects from successive pretest rounds. Reports each unit’s status in every round, whether it strengthened, weakened, or held, and which units entered or left the item set.
• compare_rounds() also compares the settings of each round and marks the comparison as not comparable when they differ. This is the audit trail the workstream called for: a status change under a changed criterion may reflect only the changed rule, and the output says so rather than letting a bookkeeping change read as progress.
• Comparisons across different workflows are refused, since status labels from different workflows rest on different criteria.
• Added expert_power(), reporting the exact probability that an item clears its expert-panel criterion at a given panel size and assumed endorsement probability, for the panel-size I-CVI guideline or the Lawshe CVR critical count. It reports the consequences of the panel sizes asked about rather than recommending one.
• expert_power() makes the I-CVI criterion’s step visible instead of smoothing it: because the guideline requires unanimity up to five experts and 0.78 from six, a fourth or fifth expert lowers the probability of clearing while a sixth raises it sharply. The plot is drawn as a step function for the same reason.
• expert_power() accepts a response_rate below 1, averaging over the realized panel size rather than assuming the invited panel arrives intact, which also captures the criterion that a smaller realized panel triggers.
• Added an as.data.frame() method for workflow objects, returning results or the scale summary as a plain data frame with a workflow column so tables from several analyses stack without losing their identity.
• Added content_report(), building a manuscript-ready table as a data frame or as Markdown for Quarto and R Markdown. Markdown is generated directly, so no reporting package is required and none is added as a dependency. Analysis settings travel with Markdown output as an attribute, and columns that are entirely missing are dropped.
• No helper is provided that returns “the items that passed.” Filtering on status is a substantive decision that belongs in the user’s own visible code, and Review never means an item must be dropped.

Interpretable output

• Printed workflow output now defines the abbreviated quantities it reports. Each flagship workflow prints a key explaining, in plain language, what its columns measure and which direction is stronger, followed by the meaning of the shared status labels and a note connecting each workflow’s own recommendation wording to them.
• Added contentvalid_glossary(), a single source of those definitions. The inline keys and the glossary read from the same table, so a term cannot be defined differently in two places.
• Inline keys can be suppressed with options(contentvalidR.show_key = FALSE) once the terminology is familiar. Substantive cautions are never suppressed by that option.
• Benchmark output now states that strength labels are percentile positions relative to published scales and are not comparable across indices. This addresses a genuine misreading: HTC is an average rating while HTD is a difference between ratings, so a scale-level HTC of 0.83 is labeled Weak in the same row where an HTD of 0.44 is labeled Very Strong. Output now explains why, rather than leaving the contrast looking like an error.
• Added a “How to Read contentvalidR Output” vignette aimed at readers meeting these methods for the first time: an annotated walkthrough of every flagship workflow’s output field by field, a section on the benchmark trap above, a list of common misreadings, and worked manuscript language that reports what the analysis does and does not establish.
• Added regression coverage asserting that interpretive wording is present and stable, that every term shown in a key is defined in the glossary, and that the documented HTC/HTD contrast still occurs in the shipped example data, so the explanation cannot drift away from the behavior it explains.

Domain coverage and content structure

• Added domain_validity(), a flagship workflow assessing whether an item set spans its intended content domain. Its results table has one row per blueprint cell, supporting construct-only or crossed construct-by-facet tables of specifications.
• Empty, thinly covered, and over-represented cells are reported against explicit, user-settable thresholds rather than silent defaults, and over-representation is documented as an attention-drawing heuristic rather than a standard. Intended item counts can be supplied through targets so expected shares come from the blueprint instead of an assumption of equal cells.
• Detecting a cell that the blueprint intends but no item addresses requires the full cell list to be supplied through domain. When it is omitted, the output states plainly that empty cells could not be detected, rather than implying full coverage.
• Added content_structure(), implementing the multidimensional scaling and hierarchical cluster analysis of expert item-similarity data described by Sireci and Geisinger (1992, 1995). Correspondence between recovered clusters and blueprint cells is quantified with the chance-corrected adjusted Rand index and reported alongside the raw cross-tabulation.
• Multidimensional scaling fit is reported across dimensionalities with Kruskal stress-1 and its conventional descriptors, documented as descriptive conventions rather than rules for deciding how many dimensions a content domain has. A requested dimensionality beyond what the similarities support is reduced and the reduction is reported.
• Added similarity_from_sort(), deriving item similarities from an item-sort task as the proportion of judges co-assigning each pair. The documentation states why this is weaker evidence than pairwise similarity ratings collected for the purpose.
• Added plot.contentvalid_structure(), drawing the expert content map with items labeled by blueprint cell.
• Weak blueprint correspondence is framed as a reason to re-examine the blueprint or item wording, explicitly not as grounds for deleting items.

Judge and rater heterogeneity

• Added judge_validity(), a flagship workflow reporting how far content-validity conclusions depend on the particular judges who served on the panel. Unlike the item-oriented workflows, its results table has one row per judge.
• Added gtheory_content(), implementing the generalizability-theory treatment of content-validity ratings in Crocker, Llabre, and Miller (1988). Reports item, judge, and residual variance components, generalizability (relative) and dependability (absolute) coefficients, and a decision study giving the panel size implied by a target coefficient.
• Added judge severity estimation from a many-facet Rasch model fitted as a logistic regression, following the generalized linear model formulation of de Boeck and Wilson (2004). Estimation is joint maximum likelihood with the standard Wright-Douglas bias correction applied and reported; the documentation states that the correction reduces rather than removes that bias, and that marginal maximum likelihood is preferable where precise calibration matters.
• Judges and items showing no variation in the dichotomized relevance decision are excluded from the facets model and reported, rather than producing infinite estimates. Because near-complete agreement is common in relevance ratings, severity in raw rating points is always reported and is used for flagging whenever the logit model is not estimable.
• Added descriptive rater-effect summaries for severity, differentiation, and central versus extreme category use, following the effects named in Engelhard (1994). Halo is deliberately not estimated from a single-dimension design, where it is not separable from low differentiation.
• Added leave-one-judge-out influence diagnostics identifying items whose CVI-based review status would change if any single judge were removed, and stating in the output that removing a judge also reduces the panel size and can therefore change the CVI criterion itself.
• Output states that a judge flagged for Review is not a judge to delete: disagreement may be substantive expertise, and the flag marks where a conclusion rests on one person’s ratings.
• Zero item-level true-score variance is now reported as a descriptive result explaining that judges did not distinguish the items, rather than as weak generalizability, and explicitly notes that a uniformly relevant item set produces the same value.

Licensing and project infrastructure

• Relicensed the source to GNU GPL version 3 only (GPL-3.0-only; R metadata GPL-3), retaining the original MIT notice in inst/NOTICE. The previously published v0.1.0 release keeps its original MIT terms; this release does not relicense it retroactively.
• Stamped citation metadata to the released version and aligned the README release-status paragraph and roadmap links with the issues and milestone they track.
• Added repository infrastructure: contributing, support, security and code-of-conduct documents, issue and pull-request templates, and pkgdown and test-coverage workflows alongside the existing check matrix.
• Replaced the completed pre-v0.1 release roadmap with an active post-release development plan, and removed the obsolete committed DESCRIPTION.bak file.
• Hardened the Ubuntu GitHub Actions setup against stale Google Chrome apt repository metadata.
• CRAN submission is deferred to v0.3.0 and tracked separately, so that the completed v0.2.0 workstreams reach users through GitHub and the R-universe without waiting on a submission round.

contentvalidR 0.1.0

First public release

• First public release of contentvalidR, providing reproducible quantitative tools for substantive and content-oriented scale pretesting.
• The recommended API centers on three complementary workflows: sort_validity() for item sorting, rating_validity() for construct ratings, and expert_validity() for relevance, essentiality, and congruence expert panels.
• Item-sort inference combines Anderson-Gerbing Psa/Csv indices with exact Howard-Melloy target-count inference and scale-level Colquitt et al. empirical interpretation benchmarks.
• Construct-rating analyses implement Hinkin-Tracey correspondence and distinctiveness, repeated-measures item screening with Greenhouse-Geisser correction, planned target-versus-orbiting contrasts, and Colquitt et al. scale-level interpretation.
• Expert-panel analyses support Aiken’s V with Penfield-Giacobbi score confidence intervals, Lawshe CVR with exact inference, CVI/modified kappa, and item-objective congruence.
• Flagship workflow objects share a stable user-facing structure, common status terminology, informative print/summary/plot methods, explicit missingness and design metadata, and restrained review recommendations.
• The release includes deterministic example data, workflow/design/reporting vignettes, manuscript-ready reporting examples, citation metadata, extensive regression and boundary-condition tests, and a cross-platform release matrix including a dedicated R-devel --as-cran NOTE-as-failure gate.
• Quantitative screening is explicitly framed as one component of a broader validity argument rather than an automatic item-retention or deletion rule.

contentvalidR 0.0.8.9000

CRAN and release hardening

• Added a dedicated CRAN-style GitHub Actions job on R-devel with NOTE-as-failure, while retaining release/oldrel/devel checks across Windows, macOS, and Linux.
• Updated the workflow to actions/checkout@v7 and current r-lib/actions@v2 conventions.
• Hardened source-package exclusions for generated pkgdown output, CRAN submission metadata, check directories, and source tarballs.
• Added a reproducible data-raw/release-check.R developer checklist covering documentation, tests, README, standard and --as-cran checks, optional URL/spelling audits, and pkgdown construction.
• Added a draft cran-comments.md for the first submission; it is excluded from the built package and must be populated with actual final check results before submission.
• Synchronized the development roadmap through v0.0.7 and moved the remaining CI/public-repository verification items into the v0.0.8 release checklist.

contentvalidR 0.0.7.9000

Documentation and reproducibility

• Added five deterministic, human-readable example datasets for item-sort, construct-rating, and all three expert-panel tasks, plus a base-R data-raw/ provenance script that regenerates them.
• Added a manuscript-ready reporting vignette with conservative methods/results scaffolds, reproducibility guidance, and examples of language that avoids treating statistical review flags as automatic validity decisions.
• Added inst/CITATION for the package and a centralized inst/REFERENCES.bib bibliography covering the release-defining methods and verified DOIs.
• Completed missing DOI metadata in core function references for Aiken V, Hinkin-Tracey ratings, Lawshe CVR, Penfield-Giacobbi score intervals, and IOC-related sources.
• Added pkgdown reference/article organization that foregrounds the three flagship workflows and clearly separates auxiliary compatibility helpers.
• Added clean-install tests for documentation assets, example-data schemas, citation metadata, and the pkgdown/reference structure.

contentvalidR 0.0.6.9000

Stable user-facing workflow API

• Harmonized sort_validity(), rating_validity(), and expert_validity() around a common workflow-object contract: results, scale_summary, settings, design, and details, with a shared contentvalid_workflow superclass.
• Added a standardized status field (Supported, Review, Insufficient data, or Descriptive only) while preserving method-specific recommendation wording such as Retain, Strong support, and Target favored.
• Harmonized summary() objects around common counts, reviewed-item tables, scale summaries, settings, and design metadata; retained n_retain, expert scale/flagged, and rating contrasts compatibility aliases.
• Standardized design metadata for effective judge ranges and missingness reporting across item-sort, construct-rating, and expert-panel workflows.
• Standardized validation of digits and plot show_legend controls across the primary workflow methods and exact sort-power planning object.
• Added compatibility handling so pre-v0.0.6 expert workflow objects remain printable and summarizable.
• Reviewed low-level function names and retained the existing public names through v0.1.0; auxiliary diagnostic, simulation, agreement, and Q-factor helpers remain available but are not promoted as flagship workflows.
• Added API regression tests and updated README/getting-started guidance for the unified workflow contract.

contentvalidR 0.0.5.9000

Release hardening

• Added centralized validation for logical flags and column-name arguments used across public workflows.
• Hardened rating data against non-finite values, malformed/duplicated target maps, empty identifiers, and ambiguous multi-scale orbiting_r specifications.
• Added clearer safeguards for within- versus between-judge ANOVA designs and for distinctiveness analyses with fewer than two construct definitions.
• Hardened expert-panel congruence target mappings, Aiken/CVI/CVR/IOC missing-data flags, alpha/seed/bootstrap inputs, and Colquitt benchmark input handling.
• Added defensive validation to legacy/auxiliary Q-factor, agreement, and simulation helpers while keeping them outside the recommended workflow surface.
• Added a dedicated v0.0.5 regression suite for malformed inputs, degenerate designs, legacy-helper contracts, and S3 workflow return contracts.
• Added boundary-focused regression coverage for all-missing item columns, tiny expert panels, zero-variance/tied rating profiles, degenerate diagnostic 2 x 2 tables, and all-missing workflow plots.
• Hardened exact item-sort inputs against non-finite counts/probabilities, made Aiken bootstrap intervals safe for all-missing item columns, and rejected whitespace-only target labels/target-column names.
• Represented unattainable exact CVR critical counts as NA (rather than an out-of-range sentinel) and hardened regression tests against brittle error-message wording.
• Closed the v0.0.5 public-API audit with an explicit namespace/export contract and S3 registration regression tests; corrected the generated namespace snapshot so expert_validity() is available in clean installs and vignette builds.

contentvalidR 0.0.4.9000

Final visualization polish

• Deterministically stagger nearby target-scale labels on Psa/Csv and HTC/HTD evidence maps so similar scale means remain legible without manual annotation.
• Draw the exact critical-Psa planning view as an integer-N step function, with requested design points overlaid, to reflect the discrete binomial retention rule rather than implying smooth interpolation.
• Added regression tests for map-label separation and the full integer critical-Psa curve.

Visualization polish

• Tightened default axis labels and plot keys so diagnostic graphics remain readable in smaller RStudio plotting panes.
• Moved profile/expert plot keys into reserved top space and moved item-sort power keys to a low-conflict location.
• Added show_legend = FALSE to workflow plot methods for compact/custom reporting.
• Reduced map-label collisions by separating item labels from target-scale-mean labels.
• Fixed the expert-panel vignette plotting object name and aligned the item-sort vignette index title with its YAML title.

Visualization and roadmap closure

• Added correspondence-distinctiveness evidence maps for item-sort (Psa/Csv) and construct-rating (HTC/HTD) workflows, with target-scale means shown separately from item points.
• Added a Hinkin-Tracey target-versus-strongest-competitor gap plot and strengthened expert-panel plots for Aiken V/I-CVI, CVR critical values, and IOC target-versus-competitor margins.
• Added plotting for exact item-sort power and the critical observed-Psa boundary.
• Added canonical published/hand-worked reference tests, including Hinkin-Tracey Study 1 mean ratings, Polit-Beck-Owen modified kappa, and the Ayre-Scally N=10 CVR boundary.
• Closed the Anderson-Gerbing legacy-inference decision: Psa/Csv remain supported, but the obsolete critical-Csv decision rule is not exposed as an alternate workflow because Howard-Melloy is applicable to multi-choice sorts and agrees in the original two-choice case.

Expert-panel workflow and repository hygiene

• Added expert_validity() with relevance, essentiality, and congruence modes plus informative print(), summary(), and plot() methods.
• Hardened Aiken’s V and made the Penfield-Giacobbi score confidence interval the default deterministic interval; bootstrap intervals remain available.
• Extended cvr() to support item-specific panel sizes and judge-by-item 0/1 input, with exact one-sided binomial p-values and critical counts following Ayre and Scally’s revisiting of Lawshe’s method.
• Hardened ioc() input validation, duplicate detection, and missing-data reporting.
• Added common panel-size CVI guidelines to the user-facing relevance workflow while explicitly treating them as review aids rather than universal validity cutoffs.
• Updated GitHub Actions from actions/checkout@v4 to the current Node-24-compatible actions/checkout@v7 line.
• Expanded public README guidance and added a dedicated expert-panel vignette.

contentvalidR 0.0.3.9000

Modern construct-rating workflow

• Added htc() and htd() for Hinkin-Tracey definitional correspondence and distinctiveness, with explicit rating-anchor validation.
• Rebuilt anova_content() around the fully crossed within-judge design used by the Hinkin-Tracey rating procedure. The function now uses a one-way repeated- measures ANOVA with Greenhouse-Geisser corrected omnibus inference plus planned target-versus-orbiting contrasts and retains a between-judge path only for genuinely independent designs. Raw omnibus p values remain available for transparency.
• Added rating_validity() as the recommended user-facing construct-rating workflow, including strongest-competitor diagnostics, Retain/Review/ Insufficient-data screening, and narrative print/summary output.
• Extended Colquitt et al. (2019) scale-level interpretation to HTC and HTD, including focal-orbiting-correlation-conditional norms and expert-judge suppression.
• Added plot.contentvalid_rating() for dependency-free HTC/HTD item plots.
• Added a dedicated Hinkin-Tracey-to-Colquitt vignette and expanded tests for rating indices, repeated-measures inference, incomplete profiles, and user-facing output.

contentvalidR 0.0.2.9000

Modern item-sort workflow

• Added Colquitt et al. (2019) empirical Psa/Csv interpretation bands, including overall and focal-orbiting-correlation-conditional norms.
• Colquitt labels are applied to target-scale averages, matching how the published norms were constructed, rather than being presented as validated item-level cutoffs.
• sort_validity() now reports target-scale definitional correspondence and distinctiveness alongside Howard-Melloy item-level Retain/Review decisions.
• Added optional focal-orbiting correlations and explicit naive/expert judge handling; Colquitt norms are suppressed for expert panels.
• compute_csv() now reports the strongest competing construct(s), making item confusion easier to diagnose.
• Added sort_power() for exact binomial design/power planning.
• Added plot.contentvalid_sort() for dependency-free item-level Psa/Csv plots.
• Added a dedicated item-sort vignette and expanded regression tests.

contentvalidR 0.0.1.9000

Methodological foundation

• Fixed compute_csv() when all non-target assignments fall in a single construct; unanimous assignment to the same wrong construct now correctly yields Csv = -1.
• compute_psa() and compute_csv() now use non-missing itemwise denominators, report n_total, n, and n_missing, and validate duplicate item-rater rows and inconsistent target mappings.
• Corrected Polit-Beck-Owen modified kappa in cvi() to use the probability of exactly A agreements, and added S-CVI/UA plus item-specific effective judge counts.
• Corrected confusion-matrix orientation in signal_detection() and changed phi calculations to preserve the direction of association.
• Reproducibility diagnostics now retain a full 2 x 2 table even when a decision level is absent.
• Clarified csv_binom_test() as exact Howard-Melloy target-count inference and added the critical target-assignment count to its output.
• Added sort_validity() as the first recommended user-facing workflow, with classed results, informative print()/summary() methods, and restrained Retain/Review/Insufficient-data recommendations.
• Replaced the placeholder unit test with substantive regression and edge-case tests.
• Consolidated GitHub Actions into one cross-platform R CMD check workflow and removed an obsolete workflow that tested unsupported R versions.