{ "_id": "6a101902acfb0bcc41c85cdb", "Package": "BayesianMCPMod", "Title": "Simulate, Evaluate, and Analyze Dose Finding Trials with\nBayesian MCPMod", "Version": "1.3.2", "Authors@R": "c(\nperson(\"Boehringer Ingelheim Pharma GmbH & Co. KG\", role = c(\"cph\", \"fnd\")),\nperson(\"Stephan\", \"Wojciekowski\", , \"stephan.wojciekowski@boehringer-ingelheim.com\", role = c(\"aut\", \"cre\")),\nperson(\"Lars\", \"Andersen\", , \"lars.andersen@boehringer-ingelheim.com\", role = \"aut\"),\nperson(\"Jonas\", \"Schick\", , \"jonas.schick@boehringer-ingelheim.com\", role = \"ctb\"),\nperson(\"Sebastian\", \"Bossert\", , \"sebastian.bossert@boehringer-ingelheim.com\", role = \"aut\")\n)", "Description": "Bayesian MCPMod (Fleischer et al. (2022)\n) is an innovative method that improves\nthe traditional MCPMod by systematically incorporating\nhistorical data, such as previous placebo group data. This\npackage offers functions for simulating, analyzing, and\nevaluating Bayesian MCPMod trials with normally and binary\ndistributed endpoints. It enables the assessment of trial\ndesigns incorporating historical data across various true\ndose-response relationships and sample sizes. Robust mixture\nprior distributions, such as those derived with the\nMeta-Analytic-Predictive approach (Schmidli et al. (2014)\n), can be specified for each dose\ngroup. Resulting mixture posterior distributions are used in\nthe Bayesian Multiple Comparison Procedure and modeling steps.\nThe modeling step also includes a weighted model averaging\napproach (Pinheiro et al. (2014) ).\nEstimated dose-response relationships can be bootstrapped and\nvisualized.", "License": "Apache License (>= 2)", "URL": "https://boehringer-ingelheim.github.io/BayesianMCPMod/,\nhttps://github.com/Boehringer-Ingelheim/BayesianMCPMod", "BugReports": "https://github.com/Boehringer-Ingelheim/BayesianMCPMod/issues", "VignetteBuilder": "knitr", "Config/testthat/edition": "3", "Encoding": "UTF-8", "Language": "en-US", "Roxygen": "list(markdown = TRUE)", "RoxygenNote": "7.3.2", "Config/pak/sysreqs": "cmake make libicu-dev libx11-dev zlib1g-dev", "Repository": "https://boehringer-ingelheim.r-universe.dev", "Date/Publication": "2026-05-14 19:19:36 UTC", "RemoteUrl": "https://github.com/boehringer-ingelheim/bayesianmcpmod", "RemoteRef": "HEAD", "RemoteSha": "d234ace44eba6162602fb4657b19498b7a459947", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-14 19:44:42 UTC", "User": "root" }, "Author": "Boehringer Ingelheim Pharma GmbH & Co. KG [cph, fnd],\nStephan Wojciekowski [aut, cre],\nLars Andersen [aut],\nJonas Schick [ctb],\nSebastian Bossert [aut]", "Maintainer": "Stephan Wojciekowski ", "MD5sum": "0b8d3982276b5022f72ec91ebf406e10", "_user": "boehringer-ingelheim", "_type": "src", "_file": "BayesianMCPMod_1.3.2.tar.gz", "_fileid": "cd077955c7f9d5a38222399032cdc8f557d871e65e4625da1e8bf70c784a104a", "_filesize": 1843618, "_sha256": "cd077955c7f9d5a38222399032cdc8f557d871e65e4625da1e8bf70c784a104a", "_created": "2026-05-14T19:44:42.000Z", "_published": "2026-05-22T08:51:14.714Z", "_distro": "noble", "_jobs": [ { "job": 77346941398, "time": 298, "config": "linux-devel-x86_64", "r": "4.7.0", "check": "OK", "artifact": "7003359143" }, { "job": 77346941324, "time": 261, "config": "linux-release-x86_64", "r": "4.6.0", "check": "OK", "artifact": "7003347611" }, { "job": 77346941506, "time": 223, "config": "macos-oldrel-arm64", "r": "4.5.3", "check": "OK", "artifact": "7003381695" }, { "job": 77346941400, "time": 134, "config": "macos-release-arm64", "r": "4.6.0", "check": "OK", "artifact": "7003311184" }, { "job": 77346941051, "time": 450, "config": "source", "r": "4.6.0", "check": "OK", "artifact": "7003264066" }, { "job": 77346940864, "time": 162, "config": "wasm-release", "r": "4.6.0", "check": "OK", "artifact": "7156558748" }, { "job": 77346941451, "time": 195, "config": "windows-devel", "r": "4.7.0", "check": "OK", "artifact": "7003326189" }, { "job": 77346941369, "time": 212, "config": "windows-oldrel", "r": "4.5.3", "check": "OK", "artifact": "7003332747" }, { "job": 77346941454, "time": 191, "config": "windows-release", "r": "4.6.0", "check": "OK", "artifact": "7003325054" } ], "_buildurl": "https://github.com/r-universe/boehringer-ingelheim/actions/runs/25881310255", "_status": "success", "_host": "GitHub-Actions", "_upstream": "https://github.com/boehringer-ingelheim/bayesianmcpmod", "_commit": { "id": "d234ace44eba6162602fb4657b19498b7a459947", "author": "wojcieko ", "committer": "wojcieko ", "message": "CRAN preparation\n", "time": 1778786376 }, "_maintainer": { "name": "Stephan Wojciekowski", "email": "stephan.wojciekowski@boehringer-ingelheim.com", "login": "wojcieko", "uuid": 143178277 }, "_registered": true, "_dependencies": [ { "package": "R", "version": ">= 4.2", "role": "Depends" }, { "package": "checkmate", "role": "Imports" }, { "package": "DoseFinding", "version": ">= 1.1-1", "role": "Imports" }, { "package": "dplyr", "role": "Imports" }, { "package": "ggplot2", "role": "Imports" }, { "package": "logistf", "role": "Imports" }, { "package": "methods", "role": "Imports" }, { "package": "nloptr", "role": "Imports" }, { "package": "RBesT", "role": "Imports" }, { "package": "stats", "role": "Imports" }, { "package": "tidyr", "role": "Imports" }, { "package": "clinDR", "role": "Suggests" }, { "package": "doFuture", "role": "Suggests" }, { "package": "future.apply", "role": "Suggests" }, { "package": "kableExtra", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "MCPModPack", "role": "Suggests" }, { "package": "reactable", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" }, { "package": "spelling", "role": "Suggests" }, { "package": "testthat", "version": ">= 3.0.0", "role": "Suggests" }, { "package": "tibble", "role": "Suggests" } ], "_owner": "boehringer-ingelheim", "_selfowned": true, "_usedby": 0, "_updates": [ { "week": "2025-30", "n": 2 }, { "week": "2025-33", "n": 3 }, { "week": "2025-34", "n": 2 }, { "week": "2025-35", "n": 8 }, { "week": "2026-07", "n": 1 }, { "week": "2026-08", "n": 11 }, { "week": "2026-09", "n": 21 }, { "week": "2026-11", "n": 3 }, { "week": "2026-20", "n": 3 } ], "_tags": [ { "name": "v1.2.0", "date": "2025-08-28" }, { "name": "v1.3.0", "date": "2026-02-23" }, { "name": "v1.3.1", "date": "2026-02-26" }, { "name": "1.3.2", "date": "2026-05-14" } ], "_stars": 10, "_contributors": [ { "user": "wojcieko", "count": 211, "uuid": 143178277 }, { "user": "xyarz", "count": 74, "uuid": 64689057 }, { "user": "stevegbrooks", "count": 52, "uuid": 7553018 }, { "user": "sebastianbossert", "count": 51, "uuid": 143491427 }, { "user": "kkmann", "count": 2, "uuid": 2482236 } ], "_userbio": { "uuid": 62895628, "type": "organization", "name": "Boehringer Ingelheim", "description": "Boehringer Ingelheim is one of the world's largest pharmaceutical companies, and the largest private one. Headquartered in Ingelheim, it operates globally" }, "_downloads": { "count": 247, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/BayesianMCPMod" }, "_devurl": "https://github.com/boehringer-ingelheim/bayesianmcpmod", "_pkgdown": "https://boehringer-ingelheim.github.io/BayesianMCPMod/", "_searchresults": 7, "_rbuild": "4.6.0", "_assets": [ "extra/BayesianMCPMod.html", "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/NEWS.html", "extra/NEWS.txt", "extra/readme.html", "extra/readme.md", "manual.pdf" ], "_homeurl": "https://github.com/boehringer-ingelheim/bayesianmcpmod", "_realowner": "boehringer-ingelheim", "_cranurl": true, "_releases": [ { "version": "1.0.0", "date": "2024-01-08" }, { "version": "1.0.1", "date": "2024-04-05" }, { "version": "1.0.2", "date": "2025-02-06" }, { "version": "1.1.0", "date": "2025-03-07" }, { "version": "1.2.0", "date": "2025-08-28" }, { "version": "1.3.0", "date": "2026-02-23" }, { "version": "1.3.1", "date": "2026-02-25" }, { "version": "1.3.2", "date": "2026-05-14" } ], "_exports": [ "assessDesign", "getBootstrapQuantiles", "getBootstrapSamples", "getContr", "getCritProb", "getESS", "getMED", "getModelFits", "getPosterior", "performBayesianMCP", "performBayesianMCPMod", "simulateData" ], "_help": [ { "page": "assessDesign", "title": "assessDesign", "topics": [ "assessDesign" ] }, { "page": "getBootstrapQuantiles", "title": "getBootstrapQuantiles", "topics": [ "getBootstrapQuantiles" ] }, { "page": "getBootstrapSamples", "title": "getBootstrapSamples", "topics": [ "getBootstrapSamples" ] }, { "page": "getContr", "title": "getContr", "topics": [ "getContr" ] }, { "page": "getCritProb", "title": "getCritProb", "topics": [ "getCritProb" ] }, { "page": "getESS", "title": "getESS", "topics": [ "getESS" ] }, { "page": "getMED", "title": "getMED", "topics": [ "getMED" ] }, { "page": "getModelFits", "title": "getModelFits", "topics": [ "getModelFits" ] }, { "page": "getPosterior", "title": "getPosterior", "topics": [ "getPosterior" ] }, { "page": "performBayesianMCP", "title": "performBayesianMCP", "topics": [ "performBayesianMCP" ] }, { "page": "performBayesianMCPMod", "title": "performBayesianMCPMod", "topics": [ "performBayesianMCPMod" ] }, { "page": "plot.modelFits", "title": "plot.modelFits", "topics": [ "plot.modelFits" ] }, { "page": "predict.modelFits", "title": "predict.modelFits", "topics": [ "predict.modelFits" ] }, { "page": "simulateData", "title": "simulateData", "topics": [ "simulateData" ] } ], "_readme": "https://github.com/boehringer-ingelheim/bayesianmcpmod/raw/HEAD/README.md", "_rundeps": [ "abind", "assertthat", "backports", "bayesplot", "BH", "bit", "bit64", "boot", "broom", "callr", "checkmate", "cli", "clipr", "codetools", "cpp11", "crayon", "desc", "distributional", "DoseFinding", "dplyr", "farver", "forcats", "foreach", "Formula", "formula.tools", "generics", "ggplot2", "ggridges", "glmnet", "glue", "gridExtra", "gtable", "haven", "hms", "inline", "isoband", "iterators", "jomo", "jsonlite", "labeling", "lattice", "lifecycle", "lme4", "logistf", "loo", "magrittr", "MASS", "Matrix", "matrixStats", "mgcv", "mice", "minqa", "mitml", "mvtnorm", "nlme", "nloptr", "nnet", "numDeriv", "operator.tools", "ordinal", "pan", "pillar", "pkgbuild", "pkgconfig", "plyr", "posterior", "prettyunits", "processx", "progress", "ps", "purrr", "QuickJSR", "R6", "RBesT", "rbibutils", "RColorBrewer", "Rcpp", "RcppEigen", "RcppParallel", "Rdpack", "readr", "reformulas", "reshape2", "rlang", "rpart", "rstan", "rstantools", "S7", "scales", "shape", "StanHeaders", "stringi", "stringr", "survival", "tensorA", "tibble", "tidyr", "tidyselect", "tzdb", "ucminf", "utf8", "vctrs", "viridisLite", "vroom", "withr" ], "_vignettes": [ { "source": "Simulation_Comparison.Rmd", "filename": "Simulation_Comparison.html", "title": "Comparison of Bayesian MCPMod and MCPMod", "engine": "knitr::rmarkdown", "headings": [ "Introduction", "Varying the Expected Effect for Maximum Dose", "Convergence of Power Values" ], "created": "2025-02-06 14:33:02", "modified": "2026-02-15 10:06:53", "commits": 3 }, { "source": "binary_endpoint.Rmd", "filename": "binary_endpoint.html", "title": "Trial Analysis Example of Bayesian MCPMod for Binary Data", "engine": "knitr::rmarkdown", "headings": [ "Scale Conventions in BayesianMCPMod", "Calculation of a MAP Prior", "1) Establish MAP prior (beta mixture distribution)", "2) Robustify prior", "3) Translate prior to logit scale (to approximate via normal mixture model)", "Specification of reference scale (this follows the idea of [@Neuenschwander2016]).", "Specify a prior list", "Trial Data", "Posterior Calculation", "Bayesian MCPMod Test Step", "Model Fitting and Visualization", "Assessment of the Minimally Efficacious Dose", "Additional Note" ], "created": "2026-02-15 10:06:53", "modified": "2026-05-13 20:37:26", "commits": 5 }, { "source": "analysis_normal.Rmd", "filename": "analysis_normal.html", "title": "Trial Analysis Example of Bayesian MCPMod for Continuous Data", "engine": "knitr::rmarkdown", "headings": [ "Introduction", "Calculation of a MAP Prior", "Dose-Response Model Shapes", "Trial Data", "Posterior Calculation", "Bayesian MCPMod Test Step", "Model Fitting and Visualization", "Assessment of the Minimally Efficacious Dose", "Additional Note" ], "created": "2023-10-20 09:18:22", "modified": "2026-02-23 10:47:53", "commits": 29 }, { "source": "Simulation_Example_Binary.Rmd", "filename": "Simulation_Example_Binary.html", "title": "Trial Simulation Example of Bayesian MCPMod for Binary Data", "engine": "knitr::rmarkdown", "headings": [ "Background and Data", "Calculation of a MAP Prior", "Specification of the New Trial Design", "Calculation of the Success Probabilities" ], "created": "2026-02-15 10:06:53", "modified": "2026-05-13 20:37:26", "commits": 5 }, { "source": "Simulation_Example.Rmd", "filename": "Simulation_Example.html", "title": "Trial Simulation Example of Bayesian MCPMod for Continuous Data", "engine": "knitr::rmarkdown", "headings": [ "Background and Data", "Calculation of a MAP Prior", "Specification of the New Trial Design", "Calculation of the Success Probabilities", "Assessment of the Minimally Efficacious Dose" ], "created": "2023-10-20 09:18:22", "modified": "2026-02-23 10:35:14", "commits": 18 } ], "_score": 6.954242509439325, "_indexed": true, "_nocasepkg": "bayesianmcpmod", "_universes": [ "boehringer-ingelheim", "wojcieko" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "1.3.2", "date": "2026-05-14T19:48:17.000Z", "distro": "noble", "commit": "d234ace44eba6162602fb4657b19498b7a459947", "fileid": "76fbe96b8aff9e3c3f669e5780e2086533f9edde47ba334ff8edb819bfea5d72", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/boehringer-ingelheim/actions/runs/25881310255" }, { "r": "4.6.0", "os": "linux", "version": "1.3.2", "date": "2026-05-14T19:47:44.000Z", "distro": "noble", "commit": "d234ace44eba6162602fb4657b19498b7a459947", "fileid": "cef635fd4f257589bca299c0942b2a351fdf2266a62687a70276566802945089", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/boehringer-ingelheim/actions/runs/25881310255" }, { "r": "4.5.3", "os": "mac", "version": "1.3.2", "date": "2026-05-14T19:49:27.000Z", "commit": "d234ace44eba6162602fb4657b19498b7a459947", "fileid": "b1aaa014ce522c746280dbff08574998247b5dab4604f58f05ba5fd18e640108", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/boehringer-ingelheim/actions/runs/25881310255" }, { "r": "4.6.0", "os": "mac", "version": "1.3.2", "date": "2026-05-14T19:46:29.000Z", "commit": "d234ace44eba6162602fb4657b19498b7a459947", "fileid": "0efe0ceba2cdfad5bf619c95b8f8e683d9b6d36ef04a33da3855b6a48da1af67", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/boehringer-ingelheim/actions/runs/25881310255" }, { "r": "4.7.0", "os": "win", "version": "1.3.2", "date": "2026-05-14T19:46:19.000Z", "commit": "d234ace44eba6162602fb4657b19498b7a459947", "fileid": "6759c97e60c2b2dfcd14247aaacfe50b6424fbdd74a66451ae0fb588cf451489", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/boehringer-ingelheim/actions/runs/25881310255" }, { "r": "4.5.3", "os": "win", "version": "1.3.2", "date": "2026-05-14T19:46:42.000Z", "commit": "d234ace44eba6162602fb4657b19498b7a459947", "fileid": "e79a0a6dce53ebcef452e85e6501461e8d85baabae1f5e288942c7eceaca77e0", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/boehringer-ingelheim/actions/runs/25881310255" }, { "r": "4.6.0", "os": "win", "version": "1.3.2", "date": "2026-05-14T19:46:16.000Z", "commit": "d234ace44eba6162602fb4657b19498b7a459947", "fileid": "40842d056fc2da7b116da91d340708710c546c35fe728d7d24c365eaeaaf5f82", "status": "success", "check": "OK", "buildurl": "https://github.com/r-universe/boehringer-ingelheim/actions/runs/25881310255" }, { "r": "4.6.0", "os": "wasm", "version": "1.3.2", "date": "2026-05-22T08:50:53.000Z", "commit": "d234ace44eba6162602fb4657b19498b7a459947", "fileid": "3dbf6e2b33fe31da83e896569aa14621fddf18cb2d07f6346c58beda82f8e9e2", "status": "success", "buildurl": "https://github.com/r-universe/boehringer-ingelheim/actions/runs/25881310255" } ] }