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BayesPPDSurv (version 1.0.3)

Bayesian Power Prior Design for Survival Data

Description

Bayesian power/type I error calculation and model fitting using the power prior and the normalized power prior for proportional hazards models with piecewise constant hazard. The methodology and examples of applying the package are detailed in . The Bayesian clinical trial design methodology is described in Chen et al. (2011) , and Psioda and Ibrahim (2019) . The proportional hazards model with piecewise constant hazard is detailed in Ibrahim et al. (2001) .

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Version

Install

install.packages('BayesPPDSurv')

Monthly Downloads

168

Version

1.0.3

License

GPL (>= 3)

Maintainer

Yueqi Shen

Last Published

April 9th, 2024

Functions in BayesPPDSurv (1.0.3)

melanoma

Melanoma Clinical Trials E1684 and E1690
BayesPPDSurv-package

Bayesian sample size determination using the power and normalized power prior for survival data
power.phm.random.a0

Power/type I error calculation for the proportional hazards model with piecewise constant hazard and random a0
phm.random.a0

Model fitting for the proportional hazards model with piecewise constant hazard and random a0
approximate.prior.beta

Approximating the normalized power prior for \(\beta\) for the proportional hazards model with piecewise constant hazard and random a0
phm.fixed.a0

Model fitting for the proportional hazards model with piecewise constant hazard and fixed a0
power.phm.fixed.a0

Power/type I error calculation for the proportional hazards model with piecewise constant hazard and fixed a0