Spending function overview
                        4.0: Spending function overview
Wang-Tsiatis Bounds     5.0: Wang-Tsiatis Bounds
checkScalar             6.0 Utility functions to verify variable
                        properties
eEvents                 Expected number of events for a time-to-event
                        study
gsBinomialExact         3.4: One-Sample Exact Binomial Boundary
                        Crossing Probabilities
gsBound                 2.7: Boundary derivation - low level
gsBoundCP               2.5: Conditional Power at Interim Boundaries
gsBoundSummary          2.8: Bound Summary and Z-transformations
gsCP                    2.4: Conditional and Predictive Power, Overall
                        and Conditional Probability of Success
gsDensity               2.6: Group sequential design interim density
                        function
gsDesign                2.1: Design Derivation
gsDesign package overview
                        1.0 Group Sequential Design
gsProbability           2.2: Boundary Crossing Probabilities
nNormal                 Normal distribution sample size (2-sample)
nSurv                   Advanced time-to-event sample size calculation
nSurvival               3.4: Time-to-event sample size calculation
                        (Lachin-Foulkes)
normalGrid              3.1: Normal Density Grid
plot.gsDesign           2.3: Plots for group sequential designs
sfExponential           4.3: Exponential Spending Function
sfHSD                   4.1: Hwang-Shih-DeCani Spending Function
sfLDOF                  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
sfPoints                4.5: Pointwise Spending Function
sfPower                 4.2: Kim-DeMets (power) Spending Function
sfTDist                 4.8: t-distribution Spending Function
sfTruncated             4.7a: Truncated, trimmed and gapped spending
                        functions
ssrCP                   Sample size re-estimation based on conditional
                        power
testBinomial            3.2: Testing, Confidence Intervals, Sample Size
                        and Power for Comparing Two Binomial Rates
