NEWS

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FastSurvival 0.2.0

• New estimation and testing functions:
  • rmst_fast(): restricted mean survival time for a single group or a two-group comparison (difference and ratio contrasts), integrating the Kaplan-Meier survival step function in a single C++ scan.
  • milestone_fast(): two-group comparison of Kaplan-Meier survival at a milestone timepoint, with Wald, log-log, and MOVER inference methods.
  • maxcombo_fast(): max-combo test over a set of Fleming-Harrington weighted log-rank statistics, with the joint p-value obtained from the implied multivariate normal distribution.
  • rmw_fast(): robust modestly-weighted log-rank test of Magirr and Öhrn, the maximum of the standard log-rank and a modestly-weighted log-rank statistic, with the joint p-value obtained from the implied bivariate normal distribution.
  • ahsw_fast(): average hazard with survival weight of Uno and Horiguchi, reporting the ratio (RAH) and difference (DAH) contrasts.
  • ahr_fast(): Kalbfleisch-Prentice average hazard ratio between two groups over a restricted interval, the estimator used by Dormuth et al. (2024) for sample-size calculation under non-proportional hazards, with a test on the group-share scale and an equivalent test and confidence interval on the log scale.
• survdiff_fast() gains weighted log-rank tests (Fleming-Harrington, modestly-weighted, Gehan-Breslow, Tarone-Ware) and stratified and stratified-weighted variants, all sharing the single-scan C++ backend.
• New simulation layer:
  • simdata_fast() extended with optional subgroups defined by a prevalence specification and a flexible accrual specification: a.rate gives absolute accrual rates (with the end of an open final interval solved from the total when a trailing rate is supplied) and a.prop gives accrual proportions, with deterministic per-interval accrual counts. The entire generation pipeline runs in a single C++ kernel that materializes the output data frame once.
  • analysis_fast(): interim or sequential analysis of simulated data at one or more looks, defined by target event counts or calendar times, computed by a fused C++ kernel that reuses the analysis cores of the standalone functions. Supports subgroup analyses.
  • simsummary_fast(): operating-characteristic summary (rejection and futility rates, stopping-look distribution, expected timing) from analysis_fast() output and supplied group-sequential boundaries, with a print() method that lays the results out as a group-sequential design report.
• Each estimation and testing function has a corresponding print() method, and the print methods share a unified display format.

FastSurvival 0.1.0 (2026-05-27)

• Initial release.
• Core computations implemented in C++ via Rcpp for use inside large simulation loops.
• survfit_fast(): single-time-point Kaplan-Meier estimator with Greenwood standard error and plain / log / log-log confidence intervals. The C++ backend locates the evaluation cutoff via binary search and accumulates the Kaplan-Meier product and Greenwood variance sum in a single scan over event positions. Returns an object of class "survfit_fast" with a print() method.
• survdiff_fast(): log-rank test returning a one-sided Z-score or a two-sided chi-square statistic. The C++ backend uses a two-pointer merge scan over pooled sorted vectors, eliminating the rank construction, tabulate(), and reverse cumulative sum operations of the standard implementation. Returns an object of class "survdiff_fast" with a print() method.
• coxph_fast(): closed-form hazard ratio estimator via the Pike-Halley Estimator method with Wald confidence interval. The C++ backend performs group splitting, at-risk counting, and per-distinct-event-time accumulation in a single pass. Returns an object of class "coxph_fast" with a print() method.
• simdata_fast(): clinical trial data simulator supporting one- and two-group designs, piecewise uniform accrual, and simple and piecewise exponential survival and dropout times. C++ backends handle piecewise sampling and two-group interleaving, and random number generation uses dqrng.