Bayesian Analysis of Generalized Linear Models with Historical Data
Posterior of Bayesian hierarchical model (BHM)
Posterior of commensurate prior (CP)
Posterior of latent exchangeability prior (LEAP)
Log marginal likelihood of an accelerated failure time (AFT) model und...
Log marginal likelihood of an accelerated failure time (AFT) model und...
Log marginal likelihood of an accelerated failure time (AFT) model und...
Log marginal likelihood of an accelerated failure time (AFT) model und...
Log marginal likelihood of a mixture cure rate (CurePWE) model under t...
Log marginal likelihood of a mixture cure rate (CurePWE) model under n...
Posterior of latent exchangeability prior (LEAP)
Log marginal likelihood of a GLM under commensurate prior (CP)
Log marginal likelihood of a GLM under latent exchangeability prior (L...
Log marginal likelihood of a GLM under meta-analytic predictive (MAP) ...
Log marginal likelihood of a piecewise exponential (PWE) model under n...
Posterior of latent exchangeability prior (LEAP)
Log marginal likelihood of a mixture cure rate (CurePWE) under the com...
Log marginal likelihood of an accelerated failure time (AFT) model und...
Log marginal likelihood of an accelerated failure time (AFT) model und...
Log marginal likelihood of an accelerated failure time (AFT) model und...
Estimate the logarithm of the normalizing constant for normalized powe...
Posterior of normalized power prior (NPP)
Posterior of a normal/half-normal prior
Posterior of power prior (PP) with fixed
Posterior of stratified power prior (PP) with fixed
Compute model averaging weights
Posterior of Bayesian hierarchical model (BHM)
Posterior of commensurate prior (CP)
Log marginal likelihood of a mixture cure rate (CurePWE) model under l...
Log marginal likelihood of a mixture cure rate (CurePWE) model under a...
Log marginal likelihood of a standard cure rate (CurePWE) model under ...
Log marginal likelihood of a mixture cure rate (CurePWE) model under t...
Estimate the logarithm of the normalizing constant for normalized powe...
Posterior of normalized power prior (NPP)
Posterior of a normal/half-normal prior
Posterior of power prior (PP) with fixed
Posterior of stratified power prior (PP) with fixed
Posterior of Bayesian hierarchical model (BHM)
Posterior of commensurate prior (CP)
Log marginal likelihood of a GLM under normalized asymptotic power pri...
Log marginal likelihood of a GLM under normalized power prior (NPP)
Log marginal likelihood of a GLM under a normal/half-normal prior
Log marginal likelihood of a GLM under power prior (PP)
Posterior of normalized asymptotic power prior (NAPP)
Estimate the logarithm of the normalizing constant for normalized powe...
Posterior of normalized power prior (NPP)
Posterior of a normal/half-normal prior
Posterior of power prior (PP) with fixed
Posterior of robust meta-analytic predictive prior (RMAP)
hdbayes: Bayesian Analysis of Generalized Linear Models with Historica...
Posterior of normalized power prior (NPP) for normal linear models
Posterior of Bayesian hierarchical model (BHM)
Posterior of commensurate prior (CP)
Posterior of latent exchangeability prior (LEAP)
Log marginal likelihood of a piecewise exponential (PWE) model under t...
Log marginal likelihood of a piecewise exponential (PWE) model under l...
Log marginal likelihood of a piecewise exponential (PWE) model under t...
Log marginal likelihood of a piecewise exponential (PWE) model under a...
Log marginal likelihood of a piecewise exponential (PWE) model under t...
Log marginal likelihood of a piecewise exponential (PWE) model under t...
Estimate the logarithm of the normalizing constant for normalized powe...
Posterior of normalized power prior (NPP)
Posterior of a normal/half-normal prior
Posterior of power prior (PP) with fixed
Posterior of stratified power prior (PP) with fixed
Sample from the ensemble posterior distribution
User-friendly functions for leveraging (multiple) historical data set(s) in Bayesian analysis of generalized linear models (GLMs) and survival models, along with support for Bayesian model averaging (BMA). The package provides functions for sampling from posterior distributions under various informative priors, including the prior induced by the Bayesian hierarchical model, power prior by Ibrahim and Chen (2000) <doi:10.1214/ss/1009212673>, normalized power prior by Duan et al. (2006) <doi:10.1002/env.752>, normalized asymptotic power prior by Ibrahim et al. (2015) <doi:10.1002/sim.6728>, commensurate prior by Hobbs et al. (2011) <doi:10.1111/j.1541-0420.2011.01564.x>, robust meta-analytic-predictive prior by Schmidli et al. (2014) <doi:10.1111/biom.12242>, latent exchangeability prior by Alt et al. (2024) <doi:10.1093/biomtc/ujae083>, and a normal (or half-normal) prior. The package also includes functions for computing model averaging weights, such as BMA, pseudo-BMA, pseudo-BMA with the Bayesian bootstrap, and stacking (Yao et al., 2018 <doi:10.1214/17-BA1091>), as well as for generating posterior samples from the ensemble distributions to reflect model uncertainty. In addition to GLMs, the package supports survival models including: (1) accelerated failure time (AFT) models, (2) piecewise exponential (PWE) models, i.e., proportional hazards models with piecewise constant baseline hazards, and (3) mixture cure rate models that assume a common probability of cure across subjects, paired with a PWE model for the non-cured population. Functions for computing marginal log-likelihoods under each implemented prior are also included. The package compiles all the 'CmdStan' models once during installation using the 'instantiate' package.