Simulation and Analysis of Adaptive Bayesian Clinical Trials
Analysis wrapper function
Beta prior for for control and treatment group
Analyzing Bayesian trial for binomial counts
Proportion of an event in control and treatment
Binomial counts for Bayesian Adaptive Trials
Data file for binomial analysis
Data file for normal analysis
Data file for survival analysis
Simulating enrollment dates
Enrollment rate wrapper
Gamma prior for for control and treatment group
Historical data for binomial distribution
Historical data for normal distribution
Historical data for survival analysis
Hypothesis wrapper
Imputation wrapper
Analyzing Bayesian trial for normal mean data
Parameters for treatment and control in normal case
Normal distribution for Bayesian Adaptive Trials
Pipe operator
Imputes time-to-event outcomes.
Simulates time-to-event outcomes.
Randomization allocation
Randomization scheme wrapper
Simulation wrapper for binomial and normal.
Details of the clinical study
Analyzing Bayesian trial for time-to-event data
Piecewise constant hazard rates and the cutpoint for control and treat...
Time-to-event outcome for Bayesian Adaptive Trials
Simulation and analysis of Bayesian adaptive clinical trials for binomial, Gaussian, and time-to-event data types, incorporates historical data and allows early stopping for futility or early success. The package uses novel and efficient Monte Carlo methods for estimating Bayesian posterior probabilities, evaluation of loss to follow up, and imputation of incomplete data. The package has the functionality for dynamically incorporating historical data into the analysis via the power prior or non-informative priors.
Useful links