{ "_id": "6a1f399eb401979e73428f23", "Package": "survextrap", "Title": "Bayesian Flexible Parametric Survival Modelling and\nExtrapolation", "Version": "1.0.1", "Date": "2026-01-11", "Authors@R": "c(person(\"Christopher\", \"Jackson\", , \"chris.jackson@mrc-bsu.cam.ac.uk\", role = c(\"aut\", \"cre\", \"cph\"),\ncomment = c(ORCID = \"0000-0002-6656-8913\")),\nperson(\"Iain\", \"Timmins\", , \"\", role = c(\"ctb\"),\ncomment = c(ORCID = \"0000-0002-8761-582X\")),\nperson(\"Michael\", \"Sweeting\", , \"\", role = c(\"ctb\"),\ncomment = c(ORCID = \"0000-0003-0980-8965\")))", "Description": "Survival analysis using a flexible Bayesian model for\nindividual-level right-censored data, optionally combined with\naggregate data on counts of survivors in different periods of\ntime. An M-spline is used to describe the hazard function, with\na prior on the coefficients that controls over-fitting.\nProportional hazards or flexible non-proportional hazards\nmodels can be used to relate survival to predictors. Additive\nhazards (relative survival) models, waning treatment effects,\nand mixture cure models are also supported. Priors can be\ncustomised and calibrated to substantive beliefs. Posterior\ndistributions are estimated using 'Stan', and outputs are\narranged in a tidy format. 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