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baselinr 0.5.0

• 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.

baselinr 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.

baselinr 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.

baselinr 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.

baselinr 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.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.