Learn R Programming

bpp (version 1.0.6)

Computations Around Bayesian Predictive Power

Description

Implements functions to update Bayesian Predictive Power Computations after not stopping a clinical trial at an interim analysis. Such an interim analysis can either be blinded or unblinded. Code is provided for Normally distributed endpoints with known variance, with a prominent example being the hazard ratio.

Copy Link

Version

Install

install.packages('bpp')

Monthly Downloads

390

Version

1.0.6

License

GPL (>= 2)

Maintainer

Kaspar Rufibach

Last Published

February 22nd, 2025

Functions in bpp (1.0.6)

bpp_2interim

Bayesian Predictive Power (BPP) for Normally Distributed Endpoint
bpp_binary

Bayesian Predictive Power (BPP) for Binary Endpoint
interval_posterior_nominator

Posterior density conditional on interim result, only known as interval, is proportional to the value of this function
bpp_continuous

Bayesian Predictive Power (BPP) for Continuous Endpoint
bpp_t2e

Bayesian Predictive Power (BPP) for Time-To-Event Endpoint
estimate_toIntegrate

Product of posterior density and conditional power for known interim result
estimate_posterior

Posterior density conditional on known interim result
estimate_posterior_nominator

Posterior density conditional on interim result is proportional to the value of this function
interval_toIntegrate2

Product of posterior density and conditional power for blinded interim result
post_power

Conditional power conditioning on a blinded interim
interval_posterior_nominator2

Posterior density conditional on two interim results, both only known as intervals, is proportional to the value of this function
interval_toIntegrate

Product of posterior density and conditional power for blinded interim result
bpp-package

Tools for Computation of Bayesian Predictive Power for a Normally Distributed Endpoint with Known Variance
basicPlot

Basic plot functions to illustrate prior and posterior densities when considering a time-to-event endpoint
NormalNormalPosterior

Normal-Normal Posterior in conjugate normal model, for known sigma
bpp

Bayesian Predictive Power (BPP) for Normally Distributed Endpoint
UniformNormalTails

Density and CDF for Uniform Distribution with Normal tails
bpp_1interim_binary

Bayesian Predictive Power (BPP) for Binary Endpoint
bpp_1interim_t2e

Bayesian Predictive Power (BPP) for Time-to-Event Endpoint
bpp_1interim_continuous

Bayesian Predictive Power (BPP) for Continuous Endpoint
bpp_1interim

Bayesian Predictive Power (BPP) for Normally Distributed Endpoint
FlatNormalPosterior

Integrand to compute Bayesian Predictive Power when flat prior has been updated with likelihood