Package index • TrialSimulator

All functions

Arms: Class of Arm
Controllers: Class of Controller
CorrelatedPfsAndOs3(): Generate Correlated PFS and OS
CorrelatedPfsAndOs4(): Generate Correlated PFS, OS and Objective Response
DynamicRNGFunction(): A wrapper of random number generator.
Endpoints: Class of Endpoint
GraphicalTesting: Class of GraphicalTesting
GroupSequentialTest: Class of GroupSequentialTest
Listeners: Class of Listener
Milestones: Class of Milestones
PiecewiseConstantExponentialRNG(): Generate Time-to-Event Endpoint from Piecewise Constant Exponential Distribution
StaggeredRecruiter(): Generate Enrollment Time from Piecewise Constant Uniform Distribution
Trials: Class of Trial
arm(): Define an Arm
calendarTime(): Triggering Condition by Calendar Time
controller(): Define a Controller
doNothing(): An Action Function that Does Nothing
endpoint(): Define Endpoints
enrollment(): Triggering Condition by Number of Randomized Patients
eventNumber(): Triggering Condition by Number of Events or Non-missing Observations of an Endpoint
fitCoxph(): Fit Cox Proportional Hazard Ratio model
fitFarringtonManning(): Farrington-Manning test for rate difference
fitLinear(): Fit linear regression model
fitLogistic(): Fit logistic regression model
fitLogrank(): Carry out log rank test
getAdaptiveDesignOutput(): Get simulation output in the vignette adaptiveDesign.Rmd
getFixedDesignOutput(): Get simulation output in the vignette fixedDesign.Rmd
listener(): Define a Listener
milestone(): Define a Milestone
plot(<milestone_time_summary>): Plot Triggering Time of Milestones in Simulated Trials
plot(<three_state_model>): Plot result of three-state ill-death model
rconst(): Generate Constant Variable
solveMixtureExponentialDistribution(): Solve Parameters in a Mixture Exponential Distribution
solveThreeStateModel(): Solve Parameters in a Three-State Ill-Death Model
summarizeDataFrame(): Summarize A Data Frame
summarizeMilestoneTime(): Summary of Milestone Time from Simulated Trials
trial(): Define a Trial
weibullDropout(): Calculate Parameters of Weibull Distribution as a Dropout Method