Clinical Trial Simulation
Check argument types, length, or dimension
Process survival data into counting process format
Create a cutting function
Create a cutting test function
Cut a dataset for analysis at a specified date
Cut a dataset for analysis at a specified event count
Zero early weighting function
Fleming-Harrington weighting function
Piecewise exponential survival estimation
Derive analysis date for interim/final analysis given multiple conditi...
Get date at which an event count is reached
MaxCombo test
Magirr and Burman weighting function
Milestone test for two survival curves
Perform multiple tests on trial data cutting
Permuted fixed block randomization
RMST difference of 2 arms
Calculate RMST for a single cut-off time point
Calculate RMST difference
The piecewise exponential distribution
Generate piecewise exponential enrollment
Simulation of fixed sample size design for time-to-event endpoint
Simulate group sequential designs with fixed sample size
Simulate a stratified time-to-event outcome randomized trial
simtrial: Clinical Trial Simulation
Convert enrollment and failure rates from sim_fixed_n() to `sim_pw_s...
Weighted logrank test
Provides some basic routines for simulating a clinical trial. The primary intent is to provide some tools to generate trial simulations for trials with time to event outcomes. Piecewise exponential failure rates and piecewise constant enrollment rates are the underlying mechanism used to simulate a broad range of scenarios such as those presented in Lin et al. (2020) <doi:10.1080/19466315.2019.1697738>. However, the basic generation of data is done using pipes to allow maximum flexibility for users to meet different needs.
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