# Group Sequential Design

## Documentation for package ‘gsDesign’ version 3.0-1

- DESCRIPTION file.
- User guides, package vignettes and other documentation.
- Package NEWS.

## Help Pages

Advanced survival sample size | Advanced time-to-event sample size calculation
binomialSPRT | 3.4: One-Sample Binomial Routines
checkLengths | 6.0 Utility functions to verify variable properties
checkRange | 6.0 Utility functions to verify variable properties
checkScalar | 6.0 Utility functions to verify variable properties
checkVector | 6.0 Utility functions to verify variable properties
ciBinomial | 3.2: Testing, Confidence Intervals, Sample Size and Power for Comparing Two Binomial Rates
condPower | Sample size re-estimation based on conditional power
eEvents | Expected number of events for a time-to-event study
Expected number of events for survival studies | Expected number of events for a time-to-event study
gsBinomialExact | 3.4: One-Sample Binomial Routines
gsBound | 2.7: Boundary derivation - low level
gsBound1 | 2.7: Boundary derivation - low level
gsBoundCP | 2.5: Conditional Power at Interim Boundaries
gsBoundSummary | 2.8: Bound Summary and Z-transformations
gsBValue | 2.8: Bound Summary and Z-transformations
gsCP | 2.4: Conditional and Predictive Power, Overall and Conditional Probability of Success
gsCPOS | 2.4: Conditional and Predictive Power, Overall and Conditional Probability of Success
gsCPz | 2.8: Bound Summary and Z-transformations
gsDelta | 2.8: Bound Summary and Z-transformations
gsDensity | 2.6: Group sequential design interim density function
gsDesign | 2.1: Design Derivation
gsDesign package overview | 1.0 Group Sequential Design
gsDesign print, summary and table summary functions | 2.8: Bound Summary and Z-transformations
gsHR | 2.8: Bound Summary and Z-transformations
gsPI | 2.4: Conditional and Predictive Power, Overall and Conditional Probability of Success
gsPOS | 2.4: Conditional and Predictive Power, Overall and Conditional Probability of Success
gsPosterior | 2.4: Conditional and Predictive Power, Overall and Conditional Probability of Success
gsPP | 2.4: Conditional and Predictive Power, Overall and Conditional Probability of Success
gsProbability | 2.2: Boundary Crossing Probabilities
gsRR | 2.8: Bound Summary and Z-transformations
gsSurv | Advanced time-to-event sample size calculation
hrn2z | 3.4: Time-to-event sample size calculation (Lachin-Foulkes)
hrz2n | 3.4: Time-to-event sample size calculation (Lachin-Foulkes)
isInteger | 6.0 Utility functions to verify variable properties
nBinomial | 3.2: Testing, Confidence Intervals, Sample Size and Power for Comparing Two Binomial Rates
nBinomial1Sample | 3.4: One-Sample Binomial Routines
nEvents | 3.4: Time-to-event sample size calculation (Lachin-Foulkes)
nEventsIA | Advanced time-to-event sample size calculation
nNormal | Normal distribution sample size (2-sample)
normalGrid | 3.1: Normal Density Grid
nSurv | Advanced time-to-event sample size calculation
nSurvival | 3.4: Time-to-event sample size calculation (Lachin-Foulkes)
O'Brien-Fleming Bounds | 5.0: Wang-Tsiatis Bounds
plot.binomialSPRT | 3.4: One-Sample Binomial Routines
plot.gsBinomialExact | 3.4: One-Sample Binomial Routines
plot.gsDesign | 2.3: Plots for group sequential designs
plot.gsProbability | 2.3: Plots for group sequential designs
plot.ssrCP | Sample size re-estimation based on conditional power
Plots for group sequential designs | 2.3: Plots for group sequential designs
Pocock Bounds | 5.0: Wang-Tsiatis Bounds
Power.ssrCP | Sample size re-estimation based on conditional power
print.eEvents | Expected number of events for a time-to-event study
print.gsBinomialExact | 3.4: One-Sample Binomial Routines
print.gsBoundSummary | 2.8: Bound Summary and Z-transformations
print.gsDesign | 2.8: Bound Summary and Z-transformations
print.gsProbability | 2.2: Boundary Crossing Probabilities
print.gsSurv | Advanced time-to-event sample size calculation
print.nSurv | Advanced time-to-event sample size calculation
print.nSurvival | 3.4: Time-to-event sample size calculation (Lachin-Foulkes)
sfBetaDist | 4.7: Two-parameter Spending Function Families
sfCauchy | 4.7: Two-parameter Spending Function Families
sfExponential | 4.3: Exponential Spending Function
sfExtremeValue | 4.7: Two-parameter Spending Function Families
sfExtremeValue2 | 4.7: Two-parameter Spending Function Families
sfGapped | 4.7a: Truncated, trimmed and gapped spending functions
sfHSD | 4.1: Hwang-Shih-DeCani Spending Function
sfLDOF | 4.4: Lan-DeMets Spending function overview
sfLDPocock | 4.4: Lan-DeMets Spending function overview
sfLinear | 4.6: Piecewise Linear and Step Function Spending Functions
sfLogistic | 4.7: Two-parameter Spending Function Families
sfNormal | 4.7: Two-parameter Spending Function Families
sfPoints | 4.5: Pointwise Spending Function
sfPower | 4.2: Kim-DeMets (power) Spending Function
sfStep | 4.6: Piecewise Linear and Step Function Spending Functions
sfTDist | 4.8: t-distribution Spending Function
sfTrimmed | 4.7a: Truncated, trimmed and gapped spending functions
sfTruncated | 4.7a: Truncated, trimmed and gapped spending functions
simBinomial | 3.2: Testing, Confidence Intervals, Sample Size and Power for Comparing Two Binomial Rates
Spending function overview | 4.0: Spending function overview
spendingFunction | 4.0: Spending function overview
ssrCP | Sample size re-estimation based on conditional power
summary.gsDesign | 2.8: Bound Summary and Z-transformations
summary.spendfn | 4.0: Spending function overview
Survival sample size | 3.4: Time-to-event sample size calculation (Lachin-Foulkes)
testBinomial | 3.2: Testing, Confidence Intervals, Sample Size and Power for Comparing Two Binomial Rates
tEventsIA | Advanced time-to-event sample size calculation
varBinomial | 3.2: Testing, Confidence Intervals, Sample Size and Power for Comparing Two Binomial Rates
Wang-Tsiatis Bounds | 5.0: Wang-Tsiatis Bounds
xprint | 2.8: Bound Summary and Z-transformations
xtable.gsSurv | Advanced time-to-event sample size calculation
z2Fisher | Sample size re-estimation based on conditional power
z2NC | Sample size re-estimation based on conditional power
z2Z | Sample size re-estimation based on conditional power
zn2hr | 3.4: Time-to-event sample size calculation (Lachin-Foulkes)