Package: gsDesign2 1.1.2.24

Yujie Zhao

gsDesign2: Group Sequential Design with Non-Constant Effect

The goal of 'gsDesign2' is to enable fixed or group sequential design under non-proportional hazards. To enable highly flexible enrollment, time-to-event and time-to-dropout assumptions, 'gsDesign2' offers piecewise constant enrollment, failure rates, and dropout rates for a stratified population. This package includes three methods for designs: average hazard ratio, weighted logrank tests in Yung and Liu (2019) <doi:10.1111/biom.13196>, and MaxCombo tests. Substantial flexibility on top of what is in the 'gsDesign' package is intended for selecting boundaries.

Authors:Keaven Anderson [aut], Yilong Zhang [aut], Yujie Zhao [aut, cre], Jianxiao Yang [aut], Nan Xiao [aut], Amin Shirazi [ctb], Ruixue Wang [ctb], Yi Cui [ctb], Ping Yang [ctb], Xin Tong Li [ctb], Chenxiang Li [ctb], Hiroaki Fukuda [ctb], Hongtao Zhang [ctb], Yalin Zhu [ctb], John Blischak [ctb], Dickson Wanjau [ctb], Merck & Co., Inc., Rahway, NJ, USA and its affiliates [cph]

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gsDesign2.pdf |gsDesign2.html✨
gsDesign2/json (API)
NEWS

# Install 'gsDesign2' in R:
install.packages('gsDesign2', repos = c('https://merck.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/merck/gsdesign2/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

8.98 score 19 stars 203 scripts 378 downloads 44 exports 78 dependencies

Last updated 2 days agofrom:b93e91ffa7. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 04 2024
R-4.5-win-x86_64OKNov 04 2024
R-4.5-linux-x86_64OKNov 04 2024
R-4.4-win-x86_64OKNov 04 2024
R-4.4-mac-x86_64OKNov 04 2024
R-4.4-mac-aarch64OKNov 04 2024
R-4.3-win-x86_64OKNov 04 2024
R-4.3-mac-x86_64OKNov 04 2024
R-4.3-mac-aarch64OKNov 04 2024

Exports:ahrahr_blindedas_gtas_rtfdefine_enroll_ratedefine_fail_rateexpected_accrualexpected_eventexpected_timefixed_design_ahrfixed_design_fhfixed_design_lffixed_design_maxcombofixed_design_mbfixed_design_milestonefixed_design_rdfixed_design_rmstgs_bgs_create_armgs_design_ahrgs_design_combogs_design_npegs_design_rdgs_design_wlrgs_info_ahrgs_info_combogs_info_rdgs_info_wlrgs_power_ahrgs_power_combogs_power_npegs_power_rdgs_power_wlrgs_spending_boundgs_spending_combogs_update_ahrppwepw_infos2pweto_integerwlr_weight_1wlr_weight_fhwlr_weight_mbwlr_weight_n

Dependencies:base64encbigDbitopsbslibcachemclicolorspacecommonmarkcorpcorcpp11curldata.tabledigestdplyrevaluatefansifarverfastmapfontawesomefsgenericsggplot2gluegsDesigngtgtablehighrhtmltoolshtmlwidgetsisobandjquerylibjsonlitejuicyjuiceknitrlabelinglatticelifecyclemagrittrmarkdownMASSMatrixmemoisemgcvmimemunsellmvtnormnlmenpsurvSSpillarpkgconfigpurrrr2rtfR6rappdirsRColorBrewerRcppreactablereactRrlangrmarkdownsassscalesstringistringrsurvivaltibbletidyrtidyselecttinytexutf8V8vctrsviridisLitewithrxfunxml2xtableyaml

Quick start for NPH sample size and power

Keaven M. Anderson

Rendered fromgsDesign2.Rmdusingknitr::rmarkdownon Nov 04 2024.

Last update: 2023-07-19
Started: 2023-03-02

Readme and manuals

Help Manual

Help pageTopics
Average hazard ratio under non-proportional hazardsahr
Blinded estimation of average hazard ratioahr_blinded
Convert summary table of a fixed or group sequential design object to a gt objectas_gt as_gt.fixed_design as_gt.gs_design
Write summary table of a fixed or group sequential design object to an RTF fileas_rtf as_rtf.fixed_design as_rtf.gs_design
Define enrollment ratedefine_enroll_rate
Define failure ratedefine_fail_rate
Piecewise constant expected accrualexpected_accrual
Expected events observed under piecewise exponential modelexpected_event
Predict time at which a targeted event count is achievedexpected_time
Fixed design under non-proportional hazardsfixed_design_ahr fixed_design_fh fixed_design_lf fixed_design_maxcombo fixed_design_mb fixed_design_milestone fixed_design_rd fixed_design_rmst
Default boundary generationgs_b
Create npsurvSS arm objectgs_create_arm
Group sequential design using average hazard ratio under non-proportional hazardsgs_design_ahr
Group sequential design using MaxCombo test under non-proportional hazardsgs_design_combo
Group sequential design computation with non-constant effect and informationgs_design_npe
Group sequential design of binary outcome measuring in risk differencegs_design_rd
Group sequential design using weighted log-rank test under non-proportional hazardsgs_design_wlr
Information and effect size based on AHR approximationgs_info_ahr
Information and effect size for MaxCombo testgs_info_combo
Information and effect size under risk differencegs_info_rd
Information and effect size for weighted log-rank testgs_info_wlr
Group sequential design power using average hazard ratio under non-proportional hazardsgs_power_ahr
Group sequential design power using MaxCombo test under non-proportional hazardsgs_power_combo
Group sequential bound computation with non-constant effectgs_power_npe
Group sequential design power of binary outcome measuring in risk differencegs_power_rd
Group sequential design power using weighted log rank test under non-proportional hazardsgs_power_wlr
Derive spending bound for group sequential boundarygs_spending_bound
Derive spending bound for MaxCombo group sequential boundarygs_spending_combo
Group sequential design using average hazard ratio under non-proportional hazardsgs_update_ahr
Piecewise exponential cumulative distribution functionppwe
Average hazard ratio under non-proportional hazardspw_info
Approximate survival distribution with piecewise exponential distributions2pwe
Summary for fixed design or group sequential design objectssummary.fixed_design summary.gs_design
Rounds sample size to an even number for equal designto_integer to_integer.fixed_design to_integer.gs_design
Weight functions for weighted log-rank testwlr_weight wlr_weight_1 wlr_weight_fh wlr_weight_mb wlr_weight_n