Group Sequential Design


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Documentation for package ‘gsDesign’ version 3.0-1

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)