Package: gsDesign 3.6.4

gsDesign: Group Sequential Design

Derives group sequential clinical trial designs and describes their properties. Particular focus on time-to-event, binary, and continuous outcomes. Largely based on methods described in Jennison, Christopher and Turnbull, Bruce W., 2000, "Group Sequential Methods with Applications to Clinical Trials" ISBN: 0-8493-0316-8.

Authors:Keaven Anderson [aut, cre]

gsDesign_3.6.4.tar.gz
gsDesign_3.6.4.zip(r-4.5)gsDesign_3.6.4.zip(r-4.4)gsDesign_3.6.4.zip(r-4.3)
gsDesign_3.6.4.tgz(r-4.4-x86_64)gsDesign_3.6.4.tgz(r-4.4-arm64)gsDesign_3.6.4.tgz(r-4.3-x86_64)gsDesign_3.6.4.tgz(r-4.3-arm64)
gsDesign_3.6.4.tar.gz(r-4.5-noble)gsDesign_3.6.4.tar.gz(r-4.4-noble)
gsDesign_3.6.4.tgz(r-4.4-emscripten)gsDesign_3.6.4.tgz(r-4.3-emscripten)
gsDesign.pdf |gsDesign.html✨
gsDesign/json (API)
NEWS

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

Peer review:

Bug tracker:https://github.com/keaven/gsdesign/issues

On CRAN:

biostatisticsboundariesclinical-trialsdesignspending-functions

82 exports 49 stars 4.55 score 72 dependencies 4 dependents 13 mentions 358 scripts 2.0k downloads

Last updated 2 months agofrom:d4a9b8a7ec. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKAug 25 2024
R-4.5-win-x86_64OKAug 25 2024
R-4.5-linux-x86_64OKAug 25 2024
R-4.4-win-x86_64OKAug 25 2024
R-4.4-mac-x86_64OKAug 25 2024
R-4.4-mac-aarch64OKAug 25 2024
R-4.3-win-x86_64OKAug 25 2024
R-4.3-mac-x86_64OKAug 25 2024
R-4.3-mac-aarch64OKAug 25 2024

Exports:%>%as_gtas_rtfas_tablebinomialSPRTcheckLengthscheckRangecheckScalarcheckVectorciBinomialcondPowereEventsgsBinomialExactgsBoundgsBound1gsBoundCPgsBoundSummarygsBValuegsCPgsCPOSgsCPzgsDeltagsDensitygsDesigngsHRgsPIgsPOSgsPosteriorgsPPgsProbabilitygsRRgsSurvgsSurvCalendarhGraphhrn2zhrz2nisIntegernBinomialnBinomial1SamplenEventsnEventsIAnNormalnormalGridnSurvnSurvivalPower.ssrCPsequentialPValuesfBetaDistsfCauchysfExponentialsfExtremeValuesfExtremeValue2sfGappedsfHSDsfLDOFsfLDPococksfLinearsfLogisticsfNormalsfPointssfPowersfStepsfTDistsfTrimmedsfTruncatedsfXG1sfXG2sfXG3simBinomialspendingFunctionssrCPtestBinomialtEventsIAtoBinomialExacttoIntegervarBinomialxprintxtablez2Fisherz2NCz2Zzn2hr

Dependencies:base64encbigDbitopsbslibcachemclicolorspacecommonmarkcpp11curldigestdplyrevaluatefansifarverfastmapfontawesomefsgenericsggplot2gluegtgtablehighrhtmltoolshtmlwidgetsisobandjquerylibjsonlitejuicyjuiceknitrlabelinglatticelifecyclemagrittrmarkdownMASSMatrixmemoisemgcvmimemunsellnlmepillarpkgconfigpurrrr2rtfR6rappdirsRColorBrewerRcppreactablereactRrlangrmarkdownsassscalesstringistringrtibbletidyrtidyselecttinytexutf8V8vctrsviridisLitewithrxfunxml2xtableyaml

A cure model calendar-based design

Rendered fromPoissonMixtureModel.Rmdusingknitr::rmarkdownon Aug 25 2024.

Last update: 2024-07-10
Started: 2022-05-16

A gentle introduction to group sequential design

Rendered fromGentleIntroductionToGSD.Rmdusingknitr::rmarkdownon Aug 25 2024.

Last update: 2024-07-22
Started: 2023-07-18

Basic time-to-event group sequential design using gsSurv

Rendered fromgsSurvBasicExamples.Rmdusingknitr::rmarkdownon Aug 25 2024.

Last update: 2024-07-10
Started: 2020-04-23

Binomial SPRT

Rendered frombinomialSPRTExample.Rmdusingknitr::rmarkdownon Aug 25 2024.

Last update: 2024-07-10
Started: 2023-04-08

Conditional error spending functions

Rendered fromConditionalErrorSpending.Rmdusingknitr::rmarkdownon Aug 25 2024.

Last update: 2024-07-10
Started: 2024-07-08

Conditional power and conditional error

Rendered fromConditionalPowerPlot.Rmdusingknitr::rmarkdownon Aug 25 2024.

Last update: 2024-07-10
Started: 2024-03-26

Graphical testing for group sequential design

Rendered fromGraphicalMultiplicity.Rmdusingknitr::rmarkdownon Aug 25 2024.

Last update: 2022-10-11
Started: 2022-05-16

gsDesign package overview

Rendered fromgsDesignPackageOverview.Rmdusingknitr::rmarkdownon Aug 25 2024.

Last update: 2024-07-10
Started: 2023-09-06

Integer sample size and event counts

Keaven Anderson

Rendered fromtoInteger.Rmdusingknitr::rmarkdownon Aug 25 2024.

Last update: 2024-07-10
Started: 2023-07-18

Multiplicity graphs

Rendered fromhGraph.Rmdusingknitr::rmarkdownon Aug 25 2024.

Last update: 2022-10-11
Started: 2020-04-23

Overview of survival endpoint design

Rendered fromSurvivalOverview.Rmdusingknitr::rmarkdownon Aug 25 2024.

Last update: 2024-07-22
Started: 2020-04-23

Spending function overview

Rendered fromSpendingFunctionOverview.Rmdusingknitr::rmarkdownon Aug 25 2024.

Last update: 2024-07-10
Started: 2023-09-06

Two-sample normal sample size

Rendered fromnNormal.Rmdusingknitr::rmarkdownon Aug 25 2024.

Last update: 2024-07-22
Started: 2020-04-23

Vaccine efficacy trial design

Rendered fromVaccineEfficacy.Rmdusingknitr::rmarkdownon Aug 25 2024.

Last update: 2024-07-10
Started: 2022-05-16

Readme and manuals

Help Manual

Help pageTopics
Convert a summary table object to a gt objectas_gt as_gt.gsBinomialExactTable
Save a summary table object as an RTF fileas_rtf as_rtf.gsBinomialExactTable as_rtf.gsBoundSummary
Create a summary tableas_table as_table.gsBinomialExact
Utility functions to verify variable propertiescheckLengths checkRange checkScalar checkVector isInteger
Testing, Confidence Intervals, Sample Size and Power for Comparing Two Binomial RatesciBinomial nBinomial simBinomial testBinomial varBinomial
Sample size re-estimation based on conditional powercondPower plot.ssrCP Power.ssrCP ssrCP z2Fisher z2NC z2Z
Expected number of events for a time-to-event studyeEvents print.eEvents
One-Sample Binomial RoutinesbinomialSPRT gsBinomialExact nBinomial1Sample plot.binomialSPRT plot.gsBinomialExact print.gsBinomialExact
Boundary derivation - low levelgsBound gsBound1
Conditional Power at Interim BoundariesgsBoundCP
Conditional and Predictive Power, Overall and Conditional Probability of SuccessgsCP gsCPOS gsPI gsPOS gsPosterior gsPP
Group sequential design interim density functiongsDensity
Design DerivationgsDesign xtable.gsDesign
Boundary Crossing ProbabilitiesgsProbability print.gsProbability
Time-to-event endpoint design with calendar timing of analysesgsSurvCalendar
Create multiplicity graphs using ggplot2hGraph
Normal distribution sample size (2-sample)nNormal
Normal Density GridnormalGrid
Plots for group sequential designsplot.gsDesign plot.gsProbability
Advanced time-to-event sample size calculationgsSurv nEventsIA nSurv print.gsSurv print.nSurv tEventsIA xtable.gsSurv
Time-to-event sample size calculation (Lachin-Foulkes)hrn2z hrz2n nEvents nSurvival print.nSurvival zn2hr
Sequential p-value computationsequentialPValue
Exponential Spending FunctionsfExponential
Hwang-Shih-DeCani Spending FunctionsfHSD
Lan-DeMets Spending function overviewsfLDOF sfLDPocock
Piecewise Linear and Step Function Spending FunctionssfLinear sfStep
Two-parameter Spending Function FamiliessfBetaDist sfCauchy sfExtremeValue sfExtremeValue2 sfLogistic sfNormal
Pointwise Spending FunctionsfPoints
Kim-DeMets (power) Spending FunctionsfPower
t-distribution Spending FunctionsfTDist
Truncated, trimmed and gapped spending functionssfGapped sfTrimmed sfTruncated
Xi and Gallo conditional error spending functionssfXG sfXG1 sfXG2 sfXG3
Bound Summary and Z-transformationsgsBoundSummary gsBValue gsCPz gsDelta gsHR gsRR print.gsBoundSummary print.gsDesign summary.gsDesign xprint
Spending FunctionspendingFunction summary.spendfn
Translate survival design bounds to exact binomial boundstoBinomialExact
Translate group sequential design to integer events (survival designs) or sample size (other designs)toInteger
xtablextable