NEWS
survHC 0.1.0 (2026-10-21)
- First release: an R port of the Python package
lifelines-hc.
higher_criticism_test(), berk_jones_test(), fisher_combination_test()
and min_p_test() for two-sample right-censored survival data.
event_pvalues() and suspected_deviations() expose the per-interval
hypergeometric p-values and the intervals flagged by the Higher Criticism
threshold.
plot_pvalue_profile() draws the signed per-interval p-value profile.
- Every entry point is an S3 generic and accepts either two samples as vectors
or the usual survival formula,
Surv(time, status) ~ group, with data,
subset and na.action. cbind(time, status) ~ group and time ~ group
work without survival attached, the latter treating every observation as an
event. The first level of the grouping variable is group A, so
alternative = "greater" tests for excess hazard in the second level. The
two interfaces are tested to return bit-identical statistics and p-values;
they differ only in that the formula method applies na.action to incomplete
rows, where the vector interface rejects them.
hc_version selects the Higher Criticism variant: "dj2008" (default),
"dj2004" (equation (2) of the paper), "beta" or "star". The names and
the default match the hc_version argument of lifelines-hc and the named
methods of the Python multitest package (>= 0.2.2); all four agree with it
to machine precision.
- No dependencies beyond base R,
stats and graphics.