Skip to contents

Group Sequential Computation

For an overview of the gsDesign package, see vignette("gsDesignPackageOverview").

gsDesign() xtable(<gsDesign>)
Design Derivation
plot(<gsDesign>) plot(<gsProbability>)
Plots for group sequential designs
gsProbability() print(<gsProbability>)
Boundary Crossing Probabilities
gsBound() gsBound1()
Boundary derivation - low level
sequentialPValue()
Sequential p-value computation

Design Characterization

Normal Endpoint Design

nNormal()
Normal distribution sample size (2-sample)

Binomial Endpoint Design

ciBinomial() nBinomial() simBinomial() testBinomial() varBinomial()
Testing, Confidence Intervals, Sample Size and Power for Comparing Two Binomial Rates
summary(<gsDesign>) print(<gsDesign>) gsBoundSummary() xprint() print(<gsBoundSummary>) gsBValue() gsDelta() gsRR() gsHR() gsCPz()
Bound Summary and Z-transformations

Time-to-Event Endpoint Design

print(<nSurvival>) nSurvival() nEvents() zn2hr() hrn2z() hrz2n()
Time-to-event sample size calculation (Lachin-Foulkes)
print(<nSurv>) nSurv() tEventsIA() nEventsIA() gsSurv() print(<gsSurv>) xtable(<gsSurv>)
Advanced time-to-event sample size calculation
gsSurvCalendar()
Time-to-event endpoint design with calendar timing of analyses
summary(<gsDesign>) print(<gsDesign>) gsBoundSummary() xprint() print(<gsBoundSummary>) gsBValue() gsDelta() gsRR() gsHR() gsCPz()
Bound Summary and Z-transformations
eEvents() print(<eEvents>)
Expected number of events for a time-to-event study
toInteger()
Translate group sequential design to integer events (survival designs) or sample size (other designs)

Vaccine/Prevention Efficacy

toBinomialExact()
Translate survival design bounds to exact binomial bounds

Spending Functions

For an overview of spending functions, see vignette("SpendingFunctionOverview").

summary(<spendfn>) spendingFunction()
Spending Function
sfLDOF() sfLDPocock()
Lan-DeMets Spending function overview
sfHSD()
Hwang-Shih-DeCani Spending Function
sfPower()
Kim-DeMets (power) Spending Function
sfExponential()
Exponential Spending Function
sfLogistic() sfBetaDist() sfCauchy() sfExtremeValue() sfExtremeValue2() sfNormal()
Two-parameter Spending Function Families
sfTDist()
t-distribution Spending Function
sfLinear() sfStep()
Piecewise Linear and Step Function Spending Functions
sfPoints()
Pointwise Spending Function
sfTruncated() sfTrimmed() sfGapped()
Truncated, trimmed and gapped spending functions

Conditional and Predictive Power

gsCP() gsPP() gsPI() gsPosterior() gsPOS() gsCPOS()
Conditional and Predictive Power, Overall and Conditional Probability of Success
summary(<gsDesign>) print(<gsDesign>) gsBoundSummary() xprint() print(<gsBoundSummary>) gsBValue() gsDelta() gsRR() gsHR() gsCPz()
Bound Summary and Z-transformations
gsBoundCP()
Conditional Power at Interim Boundaries
normalGrid()
Normal Density Grid
gsDensity()
Group sequential design interim density function

Sample Size Adaption

condPower() ssrCP() plot(<ssrCP>) z2NC() z2Z() z2Fisher() Power.ssrCP()
Sample size re-estimation based on conditional power

Single Arm Binomial Design

Input Checking

checkLengths() checkRange() checkScalar() checkVector() isInteger()
Utility functions to verify variable properties

Testing multiple hypotheses

hGraph()
Create multiplicity graphs using ggplot2

Summary tables

as_table()
Create a summary table
as_gt()
Convert a summary table object to a gt object
as_rtf()
Save a summary table object as an RTF file