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gsDesign (version 3.0-1)
Group Sequential Design
Description
Derives group sequential designs and describes their properties.
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Install
install.packages('gsDesign')
Monthly Downloads
1,787
Version
3.0-1
License
GPL (>= 2)
Maintainer
Keaven Anderson
Last Published
February 1st, 2016
Functions in gsDesign (3.0-1)
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gsCP
2.4: Conditional and Predictive Power, Overall and Conditional Probability of Success
gsProbability
2.2: Boundary Crossing Probabilities
gsDensity
2.6: Group sequential design interim density function
gsDesign
2.1: Design Derivation
nSurvival
3.4: Time-to-event sample size calculation (Lachin-Foulkes)
Wang-Tsiatis Bounds
5.0: Wang-Tsiatis Bounds
gsBoundCP
2.5: Conditional Power at Interim Boundaries
gsBinomialExact
3.4: One-Sample Binomial Routines
gsBound
2.7: Boundary derivation - low level
nNormal
Normal distribution sample size (2-sample)
eEvents
Expected number of events for a time-to-event study
gsBoundSummary
2.8: Bound Summary and Z-transformations
Binomial
3.2: Testing, Confidence Intervals, Sample Size and Power for Comparing Two Binomial Rates
nSurv
Advanced time-to-event sample size calculation
sfPower
4.2: Kim-DeMets (power) Spending Function
sfTDist
4.8: t-distribution Spending Function
checkScalar
6.0 Utility functions to verify variable properties
sfLinear
4.6: Piecewise Linear and Step Function Spending Functions
sfPoints
4.5: Pointwise Spending Function
normalGrid
3.1: Normal Density Grid
sfLDOF
4.4: Lan-DeMets Spending function overview
sfHSD
4.1: Hwang-Shih-DeCani Spending Function
sfTruncated
4.7a: Truncated, trimmed and gapped spending functions
plot.gsDesign
2.3: Plots for group sequential designs
gsDesign package overview
1.0 Group Sequential Design
Spending functions
4.0: Spending function overview
sfExponential
4.3: Exponential Spending Function
ssrCP
Sample size re-estimation based on conditional power
sfLogistic
4.7: Two-parameter Spending Function Families