{"id":32204003,"url":"https://github.com/boehringer-ingelheim/bprinstrattte","last_synced_at":"2026-07-14T12:47:17.609Z","repository":{"id":163204196,"uuid":"636751213","full_name":"Boehringer-Ingelheim/BPrinStratTTE","owner":"Boehringer-Ingelheim","description":"Causal Effects in Principal Strata Defined by Antidrug Antibodies","archived":false,"fork":false,"pushed_at":"2024-04-16T17:10:59.000Z","size":94784,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-10-22T04:49:58.213Z","etag":null,"topics":["bayesian-methods","causal-inference","clinical-trial","estimand","mcmc-methods","pharmaceutical-development","principal-stratification","r-package","simulation","stan","time-to-event"],"latest_commit_sha":null,"homepage":"https://boehringer-ingelheim.github.io/BPrinStratTTE/","language":"R","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Boehringer-Ingelheim.png","metadata":{"files":{"readme":"README.Rmd","changelog":"NEWS.md","contributing":null,"funding":null,"license":"LICENSE.md","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2023-05-05T14:57:39.000Z","updated_at":"2024-04-07T22:42:36.000Z","dependencies_parsed_at":"2023-12-19T02:14:21.905Z","dependency_job_id":"dbc27119-b0eb-449c-aa79-3ae0b4eae6e9","html_url":"https://github.com/Boehringer-Ingelheim/BPrinStratTTE","commit_stats":null,"previous_names":["boehringer-ingelheim/bprinstrattte"],"tags_count":1,"template":false,"template_full_name":null,"purl":"pkg:github/Boehringer-Ingelheim/BPrinStratTTE","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Boehringer-Ingelheim%2FBPrinStratTTE","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Boehringer-Ingelheim%2FBPrinStratTTE/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Boehringer-Ingelheim%2FBPrinStratTTE/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Boehringer-Ingelheim%2FBPrinStratTTE/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Boehringer-Ingelheim","download_url":"https://codeload.github.com/Boehringer-Ingelheim/BPrinStratTTE/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Boehringer-Ingelheim%2FBPrinStratTTE/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":280382979,"owners_count":26321423,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-10-22T02:00:06.515Z","response_time":63,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["bayesian-methods","causal-inference","clinical-trial","estimand","mcmc-methods","pharmaceutical-development","principal-stratification","r-package","simulation","stan","time-to-event"],"created_at":"2025-10-22T04:49:57.474Z","updated_at":"2025-10-22T04:49:58.448Z","avatar_url":"https://github.com/Boehringer-Ingelheim.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"---\noutput: github_document\nbibliography: \"inst/references.bib\"\ncsl: \"inst/asa.csl\"\n---\n\n\u003c!-- README.md is generated from README.Rmd. Please edit that file --\u003e\n\n```{r, include = FALSE}\nknitr::opts_chunk$set(\n  collapse = TRUE,\n  comment = \"#\",\n  fig.path = \"man/figures/README-\",\n  out.width = \"100%\"\n)\n```\n\n# BPrinStratTTE \u003ca href=\"https://boehringer-ingelheim.github.io/BPrinStratTTE/\"\u003e\u003cimg src=\"man/figures/logo.svg\" align=\"right\" height=\"139\" alt=\"BPrinStratTTE website\" /\u003e\u003c/a\u003e\n\n\u003c!-- badges: start --\u003e\n[![](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](https://lifecycle.r-lib.org/articles/stages.html#experimental)\n[![CRAN status](https://www.r-pkg.org/badges/version/BPrinStratTTE)](https://CRAN.R-project.org/package=BPrinStratTTE)\n\u003c!-- badges: end --\u003e\n\nBayesian models to estimate causal effects of biological treatments on time-to-event endpoints in clinical trials with principal strata defined by the occurrence of antidrug antibodies.\n\n## Scope\n\n- The package contains functions to fit Bayesian principal stratification models and to perform clinical trial simulations to determine operating characteristics for given scenarios.\n- Two-arm clinical trials of biological therapies are considered \n  - with an intercurrent event (determining the principal stratum of interest) that can only occur in the treated arm (such as the development of antidrug antibodies), and\n  - with a time-to-event endpoint that is assumed to follow an exponential distribution.\n- Effect estimators are hazard ratios and restricted mean survival times.\n- Potential predictors of the intercurrent event can be taken into account.\n- The models are fitted by Monte Carlo Markov Chain (MCMC) sampling, they are coded in [Stan](https://mc-stan.org/) and precompiled.\n- More flexible time-to-event distributions (piecewise-exponential and Weibull) will be considered in future versions of the package.\n\n\n\n## Principal stratification methodology\n\n- Principal stratification is an approach to estimate causal effects in partitions of subjects determined by post-treatment events. It was introduced in the biostatistical literature by @Frangakis2002.\n- The ICH E9 (R1) addendum on estimands and sensitivity analysis in clinical trials proposed principal stratification as one approach to deal with intercurrent events in clinical trials (@ICHE9R1Guideline).\n- Principal stratum membership is typically not known with certainty. A Bayesian approach may be particularly suited to deal with this type of uncertainty. Following a proposal by @Imbens1997, principal stratum membership can be treated as a latent mixture variable. \n- Motivated by scientific questions arising in clinical trials of biological therapies, in this package the approach by @Imbens1997 is adapted to a specific clinical trial setting with a time-to-event endpoint and the intercurrent event only occurring in the treated group. \n- For recent reviews of applications to clinical trials see @Lipkovich2022 and @Bornkamp2021. \n\n\u003c!-- \u003cfont size=\"3\"\u003e --\u003e\nReferences: \u003cbr\u003e\n\u003cdiv id=\"refs\"\u003e\u003c/div\u003e\n\u003c!-- \u003c/font\u003e --\u003e\n\n\n## Installation\n\nThe current stable version of the package can be installed from CRAN with:\n\n```{r cran-installation, eval=FALSE}\ninstall.packages(\"BPrinStratTTE\")\n```\n\nThe development version of the package can be installed from GitHub with: \n\n```{r gh-installation, eval=FALSE}\nif (!require(\"remotes\")) {install.packages(\"remotes\")}\nremotes::install_github(\"Boehringer-Ingelheim/BPrinStratTTE\")\n```\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fboehringer-ingelheim%2Fbprinstrattte","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fboehringer-ingelheim%2Fbprinstrattte","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fboehringer-ingelheim%2Fbprinstrattte/lists"}