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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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Version

Install

install.packages('gsDesign')

Monthly Downloads

3,531

Version

3.0-1

License

GPL (>= 2)

Maintainer

Keaven Anderson

Last Published

February 1st, 2016

Functions in gsDesign (3.0-1)

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