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Changelog

Source: NEWS.md

SimtablR 3.1.0

New features

  • tb() gains big_mark and decimal_mark to control how numbers are written in the rendered table (print, as.data.frame(), as_gt(), as_flextable()). For example tb(data, x, y, big_mark = ",") renders 4391.2 as 4,391.2, and big_mark = ".", decimal_mark = "," gives the 4.391,2 convention used in many locales. Defaults ("" / ".") reproduce the previous output exactly. Both are also reachable on a computed result through fmt(result, big_mark = ..., decimal_mark = ...); raw evidence in $data is never reformatted.
  • diag_test() gains d (decimal places for the rendered table) and percent (show sensitivity, specificity, predictive values, accuracy, and prevalence as percentages). roc() gains the same d and percent switches for its cutpoint proportion columns. percent defaults to TRUE and d to 2; pass percent = FALSE for decimal proportions. Both are also reachable on a computed result through fmt(result, d = ..., percent = ...); raw evidence in $data is never rounded or scaled.
  • Likelihood ratios from diag_test() now carry asymptotic log-method confidence intervals (Simel et al. 1991; Altman 2000), computed from the Katz ratio-of-proportions standard error. The interval is NA when any confusion-matrix cell is zero; the point estimate is unchanged.
  • diag_test() results add Cohen’s kappa for index-test / reference-standard agreement, with a Fleiss, Cohen & Everitt (1969) large-sample confidence interval.

Breaking changes

Downscale (September 2026)

SimtablR 3.1 narrows its surface to the core table, regression, diagnostic, and reporting workflow. None of these functions shipped in a CRAN release.

  • Removed km() and the Kaplan-Meier engine. Use survival::survfit() directly; survtab() still covers Cox models.
  • Removed stdtab()/standardize() (marginal standardization), additive_interaction(), and subgroups().
  • Removed sampling_weights() and the weights argument of table1() and tb(). Use the survey package directly for weighted analyses.
  • Removed regtab(method = "clogit") and its strata argument. Fit matched case-control models with survival::clogit().
  • Removed the recode helpers bin(), lump_levels(), make_missing_explicit(), and set_reference(). Use base R or forcats before analysis; reference levels can also be set with ref =.
  • Removed patch(), add_pvalue(), plot_export_dim(), and simtab_report_skeleton(); simtab_theme() is now internal. Use test() on a result instead of add_pvalue().
  • check() and audit() are replaced by advise(result, audit = TRUE).
  • tb() renames stat.cont to summary (matching table1()) and drops fast, format, paired, and p.adjust. table1() drops p.adjust, paired, and smd. Set those options on the result with test(), e.g. table1(...) |> test(p.adjust = "holm", smd = TRUE). When test() is given only these options, it keeps the existing test choice.
  • roc() drops the ci argument (DeLong intervals only) and the "closest.topleft" cutpoint.
  • export_xlsx() drops sheet, machine_sheet, and dict_sheet; sheets are always named machine-readable, display, and data-dictionary.
  • Study designs accept only their canonical names (cross_sectional, cohort, case_control, cohort_person_time, cohort_time_to_event), with spaces or hyphens in place of underscores. Synonyms such as "prevalence", "risk", "rate", and "survival" are rejected.
  • register_measure(), register_rule(), list_measures(), and list_rules() are now internal. The public extension API is register_engine(), register_journal(), list_engines(), and list_journals().
  • The advice rule set shrinks from 46 to 37 rules. Rules for removed features are gone, fisher_low_expected is folded into small_expected_cells, and normality_heuristic_large_n into continuous_test_stat_choice. The ruleset version is now downscale-2026-09-23.
  • Removed the migration-3-0 and simtablr-for-spss-stata-users vignettes; a short SPSS/Stata orientation now lives in the getting-started guide.

Earlier 3.1 changes

  • Removed register_test() and list_tests(). The comparison-test registry only stored functions; no engine ever dispatched to a registered test. Built-in tests are selected with test() / test = as before.

  • Stratified tb() PR/OR no longer prints the one-off “additive change” message about Mantel-Haenszel pooling.

  • Renamed two exported verbs that masked dplyr generics when both packages were attached. compute() is now evaluate() and explain() is now why(); the S3 methods move with them (why.simtab_spec(), why.simtab_result(), why.simtab_report()). Behaviour is unchanged. No compatibility aliases are provided, so attaching SimtablR no longer masks any dplyr export. The engine contract keeps its compute field: register_engine(compute = ...) is unaffected.

  • Named change. Adjusted PR/RR on data that previously reached the modified Poisson fallback may now report a log-binomial estimate instead, and the number changes. Old behaviour: stats::glm() has no usable default initialization for a log link on a binomial family; it aborts before the first iteration with “no valid set of coefficients has been found”. SimtablR recorded that as a convergence failure and substituted modified Poisson. New behaviour: when, and only when, the unseeded fit produces no model at all, the log-binomial is retried with the conventional starting values (intercept at the marginal log risk, slopes at zero) and its estimate is reported if it converges. On epitabl, the adjusted renal-impairment RR for 365-day MACE moves from 1.825 (robust Poisson) to 1.771 (log-binomial), matching a hand-fitted stats::glm(). Scope: a model that already fitted keeps its exact numerical path and its estimates are unchanged; the retry fires only where the previous result came from an unrecoverable fit.

  • flextable and openxlsx moved from Imports to Suggests, and dplyr was removed from Imports (it is retained only as a test-only Suggests, for the regression test that keeps the summarise() unmasking guarantee honest). This cuts the recursive non-base dependency footprint from 62 packages to 12. Every affected entry point already checked for its backend at runtime and continues to raise the classed simtab_error_dependency with installation guidance, so as_flextable(), simtab_theme(), export_docx(), export_pptx(), export_xlsx(), export_regtab_xlsx(), and the journal-style flextable themes now require an explicit install.packages() on a minimal installation. Computing, printing, as.data.frame(), tidy(), glance(), as_gt(), methods prose, and reproducibility manifests are unaffected. dplyr was imported only for a %>% that no code in the package used and that was never re-exported, so its removal has no user-visible effect.

Compliance remediation and release infrastructure

  • Diagnostic LR+ and LR- now retain mathematical Inf when a positive numerator is divided by zero; an indeterminate zero-over-zero remains NA. Raw evidence stays numeric, while renderers and machine exports handle the boundary at the presentation edge.
  • Every public file writer now adds an omitted suffix, rejects an incompatible suffix, protects an existing destination by default, and replaces it only with overwrite = TRUE through a same-directory transactional write.
  • Regression and Cox results implement coef(), confint(), formula(), nobs(), and vcov() over copied model evidence. model_info() reports convergence and per-outcome failures without exposing mutable fitted models.
  • Added deterministic edge-case tests, opt-in multi-seed and scaling tests via SIMTABLR_EXTENDED_TESTS=true, unmodified-project coverage reporting, and an executable documentation contract. Advice rules are split into table, regression, ROC, data-quality, and reviewer families without changing their IDs, order, wording, deduplication, or non-blocking behavior.
  • Added contributor guidance, a Code of Conduct, package citation metadata, statistical scope and lifecycle statements, and expanded references, assumptions, edge behavior, interpretation, and runnable examples for the major analysis and grammar interfaces.
  • ROC plots now distinguish groups with both a discrete viridis palette and line type, improving accessibility without changing their stored numerical evidence.

Correctness and honest output

  • A log-binomial model that could not be fitted and one that was fitted and failed to converge are now reported as the different findings they are. Advice and as_methods() prose say “the log-binomial model could not be fitted” for the first and keep “did not converge” for the second, instead of describing every fallback as non-convergence. The distinction is recorded in result metadata as logbinomial_status.

  • Naming a built-in measure that a descriptive or bivariate table cannot compute now names the function that can: "hr" points to survtab() and "auc" to roc(). The previous advice — “register the measure with a supported estimator” — was not actionable, because all of these measures are already registered.

  • The advice raised when a declared cohort_person_time or cohort_time_to_event design resolves no effect measure now names the engine and entry point that would estimate it, and no longer describes the survival engine as unavailable. survtab() has resolved HR since 3.1.0; the message was left over from drafting.

  • Named change. A table1() adjusted effect whose model failed to converge now raises the rung-4 adjusted_effect_not_converged advice rule. Old behaviour: the engine recorded effect_converged = FALSE but nothing read it, so a separated model printed an estimate such as 1.19e23 (8.27e22 - 1.71e23) under an “Adjusted OR (95% CI)” heading with no warning. New behaviour: the reader is told the estimate is not trustworthy. Why: regtab() already warned on separation; the descriptive adjusted path did not. Healthy models are unaffected.

  • survtab() rejects a zero-event cohort with a classed simtab_error_engine instead of failing inside cox.zph() with an error naming the engine’s own locals. The proportional-hazards diagnostic is now computed defensively, so a degenerate diagnostic cannot discard the fit.

  • An all-missing event column is rejected with a classed binding error rather than passing the 0/1 check vacuously and failing later in base R.

  • Named change. tb() no longer presents an unadjusted p-value as adjusted. Old behaviour: the column was relabelled “Adjusted P-value” and $data$tests recorded the method, but a tb() table holds a single p-value and every method is the identity on a family of one, so the number never changed. New behaviour: the argument warns that it was ignored and the display stays unadjusted. Escape hatch: table1(...) |> test(p.adjust =) adjusts a real family of p-values across variables.

  • tb() warns instead of silently returning nothing when a requested effect measure cannot be estimated - an outcome with fewer than two observed levels, or a stratified request with fewer than two usable strata - and names the reason. The empty column previously read as “no association”.

  • tb() announces which outcome level a ratio measure scores as the event when the outcome has more than two levels, instead of silently collapsing to “last level versus the rest”.

  • table1() drops the grouping variable from its own adjust set with a warning. Adjusting an effect for its own outcome is degenerate and reported an odds ratio of exactly 1.00 (1.00 - 1.00) from a model that never converged.

  • p-value boundaries print at the precision the boundary itself needs: the default pval_thresh = 0.001 rendered as "<0.00" at pval_digits = 2 and "<0" at pval_digits = 0.

  • label() accepts a named character vector passed positionally (label(x, c(age = "Age"))), the form table1(labels =) and fmt(labels =) already take; it previously reported the inner names as missing.

  • The sensitivity() “requires at least one named variation” error suggested denominator("complete"), a function that does not exist, under a variation name the code rejects. It now names the supported shorthands.

  • The diag_test() methods sentence starts capitalised.

  • repro_manifest() gains design_used, a logical distinguishing a design that actually resolved measure (resolved_from == "design") from a design that is merely recorded (for example a set_design() data-frame attribute that is never consulted by resolution). Old behaviour: the manifest reported design = "cohort" alongside measure = NULL with no way to tell the design took no part in computation. New behaviour: design_used makes that explicit, and print() on the manifest notes it. design and design_source are unchanged. Added an exported design() accessor so callers no longer need to read the internal "simtablr.design" attribute directly; set_design()’s documentation now states explicitly that the data-frame form is advisory-only and does not itself resolve an effect measure (resolution has always required design = on the call or set_design() on a simtab_spec - this is a documentation and manifest fix, not a change to resolution behaviour).

  • Fixed vignettes/study-design-effect-measures.Rmd, which read the wrong internal attribute name ("simtab_design" instead of "simtablr.design", always printing NULL) and then demonstrated tb()/table1() calls that, under the always-advisory data-frame design contract above, silently never resolved the effect measure the surrounding prose claimed. The vignette now uses the design() accessor and passes design = explicitly where a measure is meant to resolve.

  • Added an as.data.frame() method for audit results, which previously failed with a generic “cannot coerce class” error. as.data.frame(advise(result, audit = TRUE)) returns the checked-rules table with a fired logical column. as.data.frame() on a general simtab_report (for example simtablr()’s output) returns a named list of per-item data.frames, mirroring the existing as_gt()/as_flextable() behaviour for reports whose items are not all the same shape.

  • print.simtab_audit() (advise(audit = TRUE) output) now wraps its Message/Citation/Fix fields to getOption("width") instead of printing lines up to 160 characters wide regardless of console width.

  • print.simtab_regtab() no longer splits a narrow console’s output into disconnected vertical column blocks (base print.data.frame’s behaviour when a table is wider than options(width)). Each row now always prints on one line; the Variable label is abbreviated with an ellipsis when the console is too narrow to show it in full, rather than letting a term’s label and its estimate land in separate, unlabelled blocks. ## Advanced visualization

  • Named change. Forest plots now resolve their axis from the effect measure instead of always using a log axis. Ratio measures (OR, RR, PR, HR, IRR) keep the log axis with the null at 1; difference-scale quantities - including regtab(exponentiate = FALSE) coefficients - now use a linear axis with the null at 0. Old behaviour: every estimate was forced onto a log scale and any estimate at or below zero was silently dropped from the plot. New behaviour: those estimates are plotted. Why: a negative log-odds coefficient is a legitimate estimate, and silently omitting it misrepresented the model. Escape hatch: plot an exponentiated result to keep the ratio presentation.

  • autoplot() now works on diag_test() results, drawing either the stored confusion matrix (type = "matrix", default) or sensitivity, specificity, and predictive values as points with their stored confidence intervals (type = "metrics"). Calibration curves are deliberately not offered: a binary index test provides no risk scale to calibrate. The existing base plot.simtab_diag() fourfold display is unchanged.

  • SimtablR plots now carry the canvas size that suits them - a forest plot grows with its row count. The new export_plot() honours that recommendation, while explicit width/height arguments always override.

Error reporting

  • Added the simtab_error_input condition class for invalid arguments at a public entry point, alongside the existing simtab_error_binding, simtab_error_spec, simtab_error_engine, simtab_error_flag, and simtab_error_render classes. Input validation in tb(), table1(), regtab(), diag_test(), roc(), and survtab() now raises classed conditions with the house x/i/v layout rather than bare stop() calls. Message text has changed; assert on the condition class rather than on prose.
  • SimtablR condition helpers now evaluate {} expressions in the calling function’s environment, so error messages can interpolate the offending value directly.
  • Added the simtab_error_dependency class, raised when a suggested package is needed but not installed.
  • Named change. Every error the package raises now carries a SimtablR condition class. Old behaviour: roughly 160 validation failures used bare stop(), so the only way to test for them was to match their prose. New behaviour: each one raises a classed condition with the house x/i/v layout. Why: a message is not an API; a class is. Migration: message text has changed throughout - assert on the class (expect_error(..., class = "simtab_error_input")) rather than on wording. Note that cli renders argument names with backticks, so patterns matching the old 'arg' quoting no longer match. The single remaining bare stop() is in the autocomplete handler, where erroring is how the completer declines a token rather than a failure the user sees; a regression test keeps it the only one.

Statistical corrections

  • Diagnostic likelihood ratios now distinguish a defined infinite boundary from an undefined ratio. diag_test() returns Inf for LR+ or LR- when a positive numerator is divided by zero, and retains NA for zero divided by zero. Raw result and tidy values remain numeric; display and spreadsheet renderers represent infinity only at the presentation edge.

Export safety

  • Named change. All public file writers now protect existing files by default. export_docx(), export_pptx(), export_xlsx(), export_regtab_csv(), export_regtab_xlsx(), and export_plot() require overwrite = TRUE before replacing a destination. Missing format suffixes are added (.png is the plot default), while incompatible suffixes raise simtab_error_export.
  • File writers create a same-directory temporary artifact and publish it only after the backend succeeds. A failed write removes the temporary artifact and leaves any existing destination untouched. This intentionally replaces the former backend-dependent, sometimes silent overwrite behaviour.

Regression interoperability

  • regtab() and survtab() results now support coef(), confint(), formula(), nobs(), and vcov() over copied, link-scale model evidence. Single-outcome results return conventional values; multi-outcome results return predictably named collections, and outcome = selects one model. Unknown, ambiguous, or failed selections raise simtab_error_model.
  • Added model_info() for stable convergence, boundary, failure, sample-size, and event information. SimtablR still does not expose mutable fitted-model objects, fitted values, residuals, prediction, or forecasting; users needing those workflows should fit the underlying model package directly.

Autocomplete is now RStudio-only

  • Named change. simtab_completions(TRUE) installs the SimtablR completer in RStudio only. Old behaviour: the completer was installed on any front end, and on Rterm or radian it handed unrecognised tokens back to R’s own completion machinery. New behaviour: outside RStudio it declines to install, says why, and leaves rc.options(custom.completer) untouched. Why: handing a token back required calling an unexported utils function, which a CRAN package may not do; the alternative - installing anyway - would have left every non-SimtablR token with no completions at all. Escape hatch: none needed; declining changes nothing about how SimtablR itself behaves, and completion in unsupported hosts works exactly as it did before the completer existed.
  • The reported mode is now "throw" or "unsupported"; the former "delegate" mode has been removed.

Default-resolution hardening

  • The 2x2 routing guard is now an exact identical(dim(tab), c(2L, 2L)) check rather than all(dim(tab) == c(2, 2)), which recycled silently against higher-dimensional arrays. Tables with non-finite counts are also excluded. Numbers are unchanged for genuine 2x2 tables.
  • table1() now documents its display-denominator convention explicitly: percentages for observed categories use the non-missing denominator, the “Missing” row reports a raw count rather than a percentage of the column total, and association tests are identical whether or not missingness is displayed.

Extension and reproducibility infrastructure

  • Added the public evidence verb engine(). Registered engines can now be selected on either a simtab_spec or a computed simtab_result; result edits recompute through the shared verb-closure path and retain data-drift warnings.
  • digest is now an imported dependency. Captured-data fingerprints and reproducibility manifests always use and identify xxhash64; the former weak fallback fingerprint has been removed.

set_summary() replaces the conflicting summarise() builder verb

  • This is an intentional breaking API change: use set_summary("mean"), set_summary("median"), or set_summary("auto") when configuring a SimtablR specification or result. SimtablR’s former summarise() generic has been removed completely, including its export and S3 methods.
  • The rename prevents SimtablR from masking dplyr::summarise(). Previously, attaching SimtablR after dplyr broke ordinary data-frame summaries, while attaching dplyr after SimtablR broke SimtablR’s builder dispatch.

Numeric-coded categorical variables are now auto-detected

  • tb() and table1() no longer summarise every numeric column as continuous. A numeric variable is now treated as categorical when all its non-missing values are whole numbers and either exactly two distinct values exist (0/1 dummies, 1/2 sex codes – at any sample size) or at most seven distinct values exist with at least 20 non-missing observations (Likert-type codes). This boundary matches the existing ordinal_as_continuous advice rule, so the default detection now agrees with the package’s own advice. tb() announces the automatic choice with a message, and var.type overrides it in either direction.
  • table1() gains a var.type argument (scalar or per-variable named vector), matching tb(), as the escape hatch for the new default.
  • Integer codes with many levels (e.g. numeric study-site or project IDs) are still detected as continuous – no cardinality threshold can separate them from genuine counts. Convert such columns with factor() or pass var.type = "categorical".
  • Regression machinery (regtab(), adjusted effects, focus terms) keeps the strict numeric-means-continuous rule, so model terms and estimates are unchanged.

SimtablR 3.0.0

SimtablR 3.0.0 is a major release and a deliberate clean break from the 2.x series. It reorganises the package around a single grammar of table specifications and immutable result objects, adds survival/Firth/E-value engines, a suite of workflow verbs, and aligns several statistical defaults with current epidemiological practice. See vignette("migration-3-0") for a full migration guide with the escape hatch for every changed default that has one (three of the changes are correctness fixes with no escape hatch by design).

Progressive advice display

  • Automatic advice now uses one grouped cli message callout per result or report, ordered from highest to lowest severity. The concise prose omits internal rule IDs, rung labels, Fix: prefixes, and SimtablR-internal citations while preserving the complete structured advice record.
  • The default profile shows severity 3–4 advice and reports how many severity 1–2 notes are hidden. The new important profile shows severity 3–4 only; quiet is now its compatibility alias, correcting the previous behavior that retained only severity 1 advice. teaching shows all non-audit advice with external citations and rationale, while strict shows it in compact prose.
  • Advice display can be disabled with simtablr_guidance("off"), standard suppressMessages(), or knitr’s message = FALSE; stored advice is unchanged.
  • Advice now prints as one titled cli callout: a warning heading when any displayed entry has severity 3–4, and an information heading otherwise. Each callout shows only one action hint. Guidance hints now explain that simtablr_guidance() is run separately before printing, and misplaced calls inside table1() or tb() receive a targeted error.
  • When a result has only one non-audit advice entry, the entry itself is now shown under every guidance profile except "off"; it is no longer replaced by a singular hidden-note count.

Compact result printing

  • table1 and regtab results now print the table without their decorative summary and Call: lines by default. Use print(x, details = TRUE) to restore both. Stored calls, report item headings, exports, and other engine printers are unchanged.

Breaking changes

Result classes were renamed

  • Every result now carries a namespaced simtab_* class first, so SimtablR’s S3 methods dispatch only on names it owns: tb() -> c("simtab_tb", "tb", "simtab_result", "simtab"), regtab() -> c("simtab_regtab", "regtab", ...), diag_test() -> c("simtab_diag", "diag_test", ...), table1() -> c("simtab_table1", "simtab_result", "simtab"), roc() -> c("simtab_roc", "simtab_result", "simtab").
  • The bare legacy tags tb, regtab, and diag_test are kept for users’ inherits() checks. The bare tags table1 and roc are dropped because they collide with the CRAN table1 package and pROC::roc. Test the preset with is_simtab(x, "table1") / is_simtab(x, "roc") instead of inherits().

The p flag was reassigned

  • Bare p now adds the p-value column (equivalent to test = TRUE); it no longer means “percentage”. Use the new perc alias, or the canonical cell flag, for total/cell percentages. The first p use per session prints a one-time migration note.

Aligned statistical defaults (numbers may move)

The defaults below changed; each has an escape hatch (except the correctness fixes, which have none by design), tabulated under “Your numbers may move” at the end of this section.

  • 2x2 chi-squared tests in tb() and table1() now use the N-1 chi-squared statistic recommended by Campbell (2007), replacing base Pearson/Yates output for 2x2 tables; larger r x c tables still use classical Pearson chi-squared. Escape: test = "fisher" for an exact test.
  • Automatic 2x2 test selection now follows Campbell’s expected-cell boundary: test = TRUE uses Fisher-Irwin only when any expected cell is below 1, and keeps N-1 chi-squared otherwise (with educator advice when expected cells are between 1 and 5). This retires the previous expected-counts-below-5 Fisher auto-switch. Escape: test = "fisher" or test = "chisq".
  • Adjusted PR/RR estimates now try log-binomial regression first and fall back to modified Poisson regression with robust standard errors only when log-binomial does not converge. The estimator used is recorded in result metadata, announced when substituted, and reflected in as_methods() prose. regtab() remains family-driven and is not rerouted. Escape: none needed – the fallback reproduces the previous robust-Poisson estimate exactly.
  • Continuous summaries now default to summary = "auto" in table1() and stat.cont = "auto" in tb(), using complete-case N and skewness bands from Ghasemi & Zahediasl (2012) to choose mean (SD) for approximately symmetric variables and median (IQR) otherwise. Escape: summary = "median" / "mean" or stat.cont = "median" / "mean".
  • table1() now shows per-variable Missing rows by default, aligning descriptive tables with STROBE item 14. tb() remains opt-in via m = TRUE or the miss flag. Escape: missing = FALSE or missingness(display = FALSE).
  • Crude Prevalence/Risk Ratio (Katz) and Odds Ratio (Woolf) calculations now apply a Haldane-Anscombe +0.5 continuity correction to all four cells of a 2x2 comparison when any cell is zero, instead of returning NA. The correction is announced via a rung-1 zero_cell_correction educator rule. Affects only rows with a zero cell.

Deprecations

  • The bare flag aliases rp (-> pr) and m (-> miss) are soft-deprecated and warn once per session; they are slated for removal in 3.1.

New engines and workflow verbs

  • Added survtab() for Cox proportional hazards tables and km() for Kaplan-Meier summaries (via the survival package), with KM autoplot(), survival tidy()/glance()/as_methods() renderers, log-rank tests, Schoenfeld PH checks, and graceful install guidance. The design resolver now selects HR for cohort analyses with time and event roles.
  • Added regtab(method = "firth") for Firth penalised binomial-logit models (via logistf), including profile-penalised confidence intervals, methods prose, and separation advice pointing to a one-click refit.
  • Added e_value() for native VanderWeele-Ding E-values from ratio estimates, with OR/HR approximation flags.
  • Added subgroups() to recompute an existing effect result within levels of a subgroup variable, returning a simtab_report, reporting Breslow-Day or interaction-LRT heterogeneity, rendering a subgroup forest, and emitting subgroup-credibility/multiplicity advice.
  • Added sensitivity() to re-estimate a result under named variations (measure, denominator, …) and flow() to record the analytic sample as a participant-flow object.
  • Added explain() and as_methods() (now covering every engine) to narrate the analytic decisions and write the methods sentence from the result itself.
  • Added strobe() / stard() reporting-checklist objects (classed, with their own print method; they advise, they never grade or block) and codebook() for a one-row-per-variable data dictionary.
  • Added a classed error taxonomy – simtab_error_binding, _spec, _engine, _render, _flag, all inheriting simtab_error – documented at ?simtab_errors, so callers can catch failures by class.

Language and grammar

  • Added the shared terse flag vocabulary row, col, cell, or, pr, rr, p, and miss, enabled on both tb() and table1() (table1() reads flags from ... after by; unknown dots error as likely typos). perc is a quiet alias for cell in tb() because it reads better for univariate percentages. Named measure = and test = arguments always override flags; flags apply left-to-right.
  • Unified the binding idiom: bare names, quoted strings, and tidyselect helpers (all_of(), starts_with()) route through one path on every preset. Existing string-based code keeps working unchanged.
  • Added the simtab() builder and setter verbs; built-in presets desugar through the verbs, and every setter verb has a simtab_result method (verb closure) that re-estimates via one shared recompute helper over the result’s captured data.
  • Added the extension registry: register_engine(), register_measure(), register_test(), register_journal(), register_rule(), each with a list_*() reader. A registered engine reaches full method dispatch with zero edits to SimtablR (see vignette("customizing-extending")).

Statistical methods

  • Added forest-plot rendering for effect-carrying regtab(), tb(), table1(), and Cox results via engine-local autoplot renderers; forest data are built from raw effect numerics and are invariant to restyling/rounding.
  • regtab() now computes native GVIF/VIF-equivalent diagnostics for multi-predictor models, matching pinned car::vif() references without adding car as a dependency. Default printed/tidy/display tables are unchanged; request VIF via as.data.frame(fit, vif = TRUE) or generics::glance(fit, vif = TRUE). Advice flags VIF above 5 and escalates above 10; single-predictor models stay silent.
  • regtab(robust = ) now accepts "HC0", "HC1", "HC2", "HC3", or "none" in addition to TRUE/FALSE. A rung-2 hc0_small_n educator rule suggests robust = "HC3" at N < 100 (Long & Ervin, 2000).
  • check()/audit() now includes a standing, severity-0 regtab() prompt asking whether predictors were pre-specified (formula provenance cannot detect stepwise selection), and a rung-2 many_predictors_no_design rule fires when a regtab() formula has more than 10 predictor terms and no design was stated.
  • Added data-shape educator rules that inspect the described variable(s) directly: id_like_column, constant_column, high_cardinality_factor, ordinal_as_continuous, date_column_described, repeated_ids_independence, overdispersion_poisson, forced_mean_skewed, and tiny_denominator_pct.
  • Added survival educator rules cox_ph_violation (rung 4) and km_median_unreached (rung 1).

Corrections

  • export_docx(), export_pptx(), and as_flextable() now work for every engine result – tb(), rbind()-stacked tables, diag_test(), regtab(), roc(), and the survival tables – and accept the documented footnotes argument. Previously only table1() results exported; every other engine’s as_flextable() renderer forwarded footnotes into flextable::flextable() and errored with unused argument (footnotes = NULL).
  • The Mantel-Haenszel pooled risk-ratio confidence interval now uses the Greenland-Robins (1985) variance estimator, gate-checked against epiR and the longhand formula. Earlier drafts used an incorrect variance; stratified PR/RR confidence intervals (from tb(..., strat = ) and subgroups()) become wider and correct. The point estimate is unchanged.
  • tb() combined with the missing-display flag (miss/m) and an effect measure or the p-value now computes the effect ratios and the association test on complete cases, exactly as it does without the flag. Previously the flag’s <NA> display column was mistaken for the outcome’s event column, so tb(data, exposure, outcome, or, miss) reported a wrong odds/risk ratio plus a spurious <NA> effect row, and tb(data, exposure, outcome, p, miss) returned a corrupted chi-squared test (df = 4, NaN). The missing category is still shown in the frequency/percentage display; only the statistics are now complete-case, matching table1().
  • sensitivity() now reports the actual effect estimate for each variation instead of the reference row. Previously the headline extractor filtered reference rows with isTRUE() on a whole logical column, which collapses to a single FALSE and never removed the reference row, so every variation reported estimate = 1 with missing confidence limits regardless of the true effect.

SimtablR 2.0.0

Major Changes

tb() Function

Overhauled tb() to return a structured list. The object inherits the S3 class vector c(“tb”, “simtab”). Matrices with attributes are no longer returned directly from the primary function loop. Ratio Schema Standardization: Renamed fields within the internal ratios data frame to lower_ci and upper_ci to establish strict compatibility with multivariable regression tables (regtab()). Simplified Continuous Syntax: Enhanced var.type parsing to accept an unnamed scalar character string shorthand (e.g., var.type = “continuous”) and map it automatically to the main row variable. #### New Features Table Stacking (rbind.tb): Implemented the rbind.tb() S3 method to support the vertical stacking of discrete tb objects sharing the same column variables. Dual Export Modes: Expanded as.data.frame.tb() and as.data.frame.rbind_tb() to support a tidy toggle. tidy = FALSE (default) provides display-ready character strings for manuscripts, while tidy = TRUE returns unformatted numeric data frames optimized for ggplot2 workflows. RStudio Autocomplete Replacement: Integrated an unexported interactive completion replacement hook inside zzz.R using .rs.registerAutocompleteReplacement() to dynamically expose dataset column names inside RStudio console environments. Wald-Aligned Ratio Statistics: Upgraded unadjusted Prevalence Ratio (PR) and Odds Ratio (OR) calculations to compute Wald z-score p-values aligned directly alongside confidence intervals. Added new runtime educational message() notifications that fire automatically under specific conditions Added explicit registerS3method() entries for rbind, print, and as.data.frame generics within .onLoad() to guarantee stable dispatch across development environments, source routines, and unattached package builds. #### Other changes Fixed a vulnerability where common column names (like p or col) matching formatting flags were silently intercepted by the NSE symbol parser. *Extracted all text formatting, cell stitching matrices, margin additions, and string template processing out of core workflows and isolated them within a unified internal builder called .build_display_matrix().