Available on GitHub
BayesMFSurv with Bomin Kim and Bumba Mukherjee. URL: https://github.com/minniejoo/BayesMFSurv
This package contains functions to fit parametric (Weibull and Exponential) Misclassified-Failure Survival models via Bayesian methods, as described in Bagozzi et al (2017, working paper). The Bayesian Misclassified-Failure Model accounts for asymmetric misclassification arising within one’s failed cases. More specifically, the model is designed to accommodate situations where true censored cases are misclassified as failed observations. The package also contains auxiliary functions to calculate various statistics using model results.
The three functions in the package are:
||Fits a parametric Bayesian MF model via Markov Chain Monte Carlo to estimate the misclassification in the first stage and the hazard in the second stage.|
||Calculates the loglikelihood for fitted model objects of class bayes.mfsurv.|
||Calculates the deviance information criterion (DIC) for fitted model objects of class bayes.mfsurv.|
Packages Under Development
Bayesian Spatial Cure Model with Bomin Kim and Bumba Mukherjee.
This package presents and implements the Bayesian Spatial Cure Parametric Survival model, as described in Joo et al (2017, working paper). Functions to fit Bayesian Spatial Cure Parametric Survival models via Markov Chain Monte Carlo (MCMC) is contained in the package.
Zero- and Middle- Inflated Ordered Probit Models with Benjamin Bagozzi and Bumba Mukherjee.