BayesPIM: Bayesian Prevalence-Incidence Mixture Model
Models time-to-event data from interval-censored screening studies. It accounts for latent prevalence at baseline and incorporates misclassification due to imperfect test sensitivity. For usage details, see the package vignette ("BayesPIM_intro"). Further details can be found in T. Klausch, B. I. Lissenberg-Witte, and V. M. Coupe (2024), "A Bayesian prevalence-incidence mixture model for screening outcomes with misclassification", <doi:10.48550/arXiv.2412.16065>.
| Version: | 1.0.0 |
| Depends: | R (≥ 3.5.0),coda |
| Imports: | Rcpp,mvtnorm,MASS,ggamma,doParallel,foreach, parallel,actuar |
| LinkingTo: | Rcpp |
| Suggests: | knitr,rmarkdown |
| Published: | 2025-03-22 |
| DOI: | 10.32614/CRAN.package.BayesPIM |
| Author: | Thomas Klausch [aut, cre] |
| Maintainer: | Thomas Klausch <t.klausch at amsterdamumc.nl> |
| BugReports: | https://github.com/thomasklausch2/BayesPIM/issues |
| License: | MIT + fileLICENSE |
| URL: | https://github.com/thomasklausch2/bayespim |
| NeedsCompilation: | yes |
| Materials: | README |
| CRAN checks: | BayesPIM results |
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