Changelog
Source:NEWS.md
BayesianQDM 0.1.0
Initial Release
The initial release of BayesianQDM provides a comprehensive framework for Bayesian decision-making in clinical trials with support for both binary and continuous endpoints.
Core Functions
Binary Endpoints
-
pPPsinglebinary()- Posterior and posterior predictive probability calculation -
pGNGsinglebinary()- Go/NoGo/Gray decision probability framework -
p2betadiff()- Beta distribution differences -
p2betabinomdiff()- Beta-Binomial distribution differences -
d2betadiff()- Density function for beta distribution differences
Continuous Endpoints
-
pPPsinglecontinuous()- Posterior and posterior predictive probability calculation -
pGNGsinglecontinuous()- Go/NoGo/Gray decision probability framework - Distribution difference functions:
-
pNI2tdiff()- Numerical integration method -
pMC2tdiff()- Monte Carlo simulation method -
pWS2tdiff()- Welch-Satterthwaite approximation method
-
Utility Functions
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AppellsF1()- Appell’s hypergeometric function F1 for numerical calculations
Study Designs
- Controlled design - Standard randomized controlled trials
- Uncontrolled design - Single-arm studies with historical controls
- External control design - Power prior incorporation of historical data
Prior Distributions
- Binary endpoints - Beta priors with flexible parameterization
- Continuous endpoints - Normal-Inverse-Chi-squared conjugate priors and vague priors
Calculation Methods
- NI (Numerical Integration) - Exact calculation using convolution
- WS (Welch-Satterthwaite) - Fast approximation for unequal variances
- MC (Monte Carlo) - Simulation-based flexible approach
Documentation
- Comprehensive function documentation with examples
- Three detailed vignettes:
- Introduction to BayesianQDM
- Binary endpoints analysis
- Continuous endpoints analysis
- Complete test suite using testthat