Changes in version 0.5.0 (2026-06-30)                  

  - New wwc_summary(): collapse a baseline_equivalence() table into an
    overall WWC verdict (satisfied / satisfied_with_adjustment /
    not_satisfied) plus per-category counts and the largest absolute
    effect size.
  - New attrition(): overall and differential attrition for a two-group
    design — the inputs to the WWC attrition standard.

                        Changes in version 0.4.0                        

  - New bundled dataset tutoring: a simulated quasi-experimental
    tutoring evaluation (400 students) whose covariates span all three
    WWC equivalence categories. See data-raw/tutoring.R for how it is
    generated.
  - New vignette "An impact-evaluation workflow" walking from raw study
    data to a baseline-equivalence report, Love plot, and formatted
    table.

                        Changes in version 0.3.0                        

  - New love_plot(): a Love plot of standardized effect sizes across
    covariates, with WWC threshold reference lines and points coloured
    by category (requires ggplot2).
  - New gt_baseline(): render a baseline equivalence table as a
    formatted gt table with readable labels and rounded statistics
    (requires gt).
  - ggplot2 and gt added to Suggests; both functions error gracefully if
    the package is not installed.

                        Changes in version 0.2.0                        

  - New cox_index(): WWC Cox index standardized effect size for binary
    (dichotomous) covariates.
  - baseline_equivalence() now handles binary covariates (numeric 0/1,
    logical, or two-level factor) via the Cox index, in addition to
    continuous covariates via Hedges' g. A covariate with exactly two
    unique values is treated as binary.
  - The output gains a type column ("continuous" / "binary"), and the
    effect-size column is renamed from hedges_g to the
    estimator-agnostic effect_size (breaking change). For binary
    covariates, mean_treatment and mean_comparison report event
    proportions.
  - The default covariate set now includes logical and factor columns,
    not only numeric ones.

Roadmap

  - Formatted output for reports (gt / flextable).
  - Love plot of standardized effect sizes across covariates.

                        Changes in version 0.1.0                        

Initial scaffold.

  - hedges_g(): standardized mean difference (Hedges' g) between a
    treatment and a comparison group, with the WWC small-sample
    correction factor.
  - wwc_classify(): classify standardized mean differences into the
    three WWC baseline-equivalence categories.
  - baseline_equivalence(): build a report-ready baseline equivalence
    table for continuous covariates.