BayesPIM

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.

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