{ "_id": "6a3295b03efcd9bda438fdae", "Package": "BayesTSM", "Title": "Bayesian Progressive Three State Model with Censoring Due to\nIntervention", "Version": "1.0.1", "Authors@R": "person(\"Thomas\", \"Klausch\", , \"t.klausch@amsterdamumc.nl\", role = c(\"aut\", \"cre\"))", "Description": "In screening programs, individuals are usually followed up\nand tested (screened) for the development of a disease, such as\ncancer. The target disease often develops progressively in\nstages; for example healthy (state 1), pre-state disease (state\n2), and the disease state (state 3). When the pre-state disease\nis found during screening it is intervened upon, for example by\nsurgical removal of a lesion, so that the progression of the\npre-state disease to disease is interrupted. This is called\ncensoring due to intervention. Researchers often want to\nestimate the time from baseline to the pre-state disease, the\ntime from the pre-state disease to the disease, and the total\ntime from baseline to the disease. In addition, researchers\noften want to regress these times on baseline covariates. To\nthese ends, BayesTSM estimates a progressive three-state model\nwith censoring due to intervention using Bayesian estimation\nmethods, as described in Klausch et al. (2023)\n.", "License": "MIT + file LICENSE", "URL": "https://github.com/thomasklausch2/bayestsm", "BugReports": "https://github.com/thomasklausch2/bayestsm/issues", "Encoding": "UTF-8", "Roxygen": "list(markdown = TRUE)", "Config/roxygen2/version": "8.0.0", "VignetteBuilder": "knitr", "LazyData": "true", "Repository": "https://thomasklausch2.r-universe.dev", "Date/Publication": "2026-06-08 18:05:38 UTC", "RemoteUrl": "https://github.com/thomasklausch2/bayestsm", "RemoteRef": "HEAD", "RemoteSha": "a829278034f54e35f4ff6b9f6c34d48ba9652e6f", "NeedsCompilation": "yes", "Packaged": { "Date": "2026-06-17 12:35:45 UTC", "User": "root" }, "Author": "Thomas Klausch [aut, cre]", "Maintainer": "Thomas Klausch ", "MD5sum": "d034e6bfd466cf01dcdcc499d9215a30", "_user": "thomasklausch2", "_type": "src", "_file": "BayesTSM_1.0.1.tar.gz", "_fileid": "bf9cdfa6b3cb6e24df77fdc27cfe59c46bf6ad98f138e6c7ef58e5e42bcb9cff", "_filesize": 2584014, "_sha256": 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