<?xml version="1.0" encoding="UTF-8"?>
<oai_dc:dc xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
  <dc:title>Fast Survival Analysis and Simulation for Clinical Trials</dc:title>
  <dc:title>R package FastSurvival version 0.2.0</dc:title>
  <dc:description>Provides fast alternatives to standard survival analysis functions
    in the 'survival' package, together with tools for time-to-event trial
    simulation and sequential analysis. The estimation and testing functions
    cover a single-time-point Kaplan-Meier estimator (survfit_fast()), log-rank
    tests including weighted and stratified variants (survdiff_fast()), a
    closed-form hazard ratio estimator based on the Pike-Halley Estimator method
    (coxph_fast()), restricted mean survival time (rmst_fast()), window mean
    survival time (wmst_fast()), milestone survival comparison
    (milestone_fast()), median survival time (medsurv_fast()), the max-combo
    test (maxcombo_fast()), the robust modestly-weighted log-rank test
    (rmw_fast()), the weighted Kaplan-Meier (Pepe-Fleming) test (wkm_fast()),
    the average hazard with survival weight (ahsw_fast()), and the
    Kalbfleisch-Prentice average hazard ratio (ahr_fast()). The simulation
    layer generates individual patient data (simdata_fast()), performs interim
    or sequential analyses (analysis_fast()), and aggregates operating
    characteristics (simsummary_fast()). A visualization layer assembles
    design-stage scenarios (gen_scenario_fast()) and builds analysis-stage
    Kaplan-Meier curves (kmcurve_fast()), each with plot and print methods.
    All functions are designed for repeated
    evaluation inside large simulation loops, such as adaptive sample-size
    re-estimation, probability-of-success calculations, and regional consistency
    evaluation in multi-regional trials. Core computations are implemented in
    'C++' via 'Rcpp' for maximum performance. Methodological background is
    described in Collett (2014, ISBN:9780429196294).</dc:description>
  <dc:type>Software</dc:type>
  <dc:relation>Depends: R (&gt;= 4.1.0)</dc:relation>
  <dc:relation>Imports: graphics, grDevices, stats, dqrng, Rcpp, mvtnorm</dc:relation>
  <dc:relation>LinkingTo: Rcpp, dqrng</dc:relation>
  <dc:relation>Suggests: survival, survRM2, survAH, simtrial, gsDesign, rpact, nph,
nphRCT, microbenchmark, testthat (&gt;= 3.0.0), knitr, rmarkdown</dc:relation>
  <dc:creator>Gosuke Homma &lt;my.name.is.gosuke@gmail.com&gt;</dc:creator>
  <dc:publisher>Comprehensive R Archive Network (CRAN)</dc:publisher>
  <dc:contributor>Gosuke Homma [aut, cre]</dc:contributor>
  <dc:rights>MIT + file LICENSE (https://CRAN.R-project.org/package=FastSurvival/LICENSE)</dc:rights>
  <dc:date>2026-07-27</dc:date>
  <dc:format>application/tgz</dc:format>
  <dc:identifier>https://CRAN.R-project.org/package=FastSurvival</dc:identifier>
  <dc:identifier>doi:10.32614/CRAN.package.FastSurvival</dc:identifier>
  <dc:language>en-US</dc:language>
</oai_dc:dc>
