chestR 0.1.0
- Initial packaged release of kernel-weighted Cox regression
(
chestr) for exploring treatment effect heterogeneity on a
biomarker grid.
- Implements Kish effective-sample-size (ESS) events-per-df safeguard
(
min_events_per_df, default 10). Grid points below the
threshold are skipped with NA coefficients and flagged via
reliable.
- Exported API:
chestr(), plot.chestr() /
plot(), chestr_test().
- Weighting methods:
"distance" (default),
"square_distance", "legacy".
- Global permutation test of constant treatment effect over biomarker
space (
T_L2, T_MAX) via
chestr_test().
- Vignette
chestr-workflow demonstrates the global Cox →
chestr → plot workflow (and optional permutation test) on simulated
survival data.