{ "_id": "6a23e429530b9bc726be85ec", "Package": "BayesCTDesign", "Type": "Package", "Title": "Two Arm Bayesian Clinical Trial Design with and Without\nHistorical Control Data", "Version": "0.6.1", "Authors@R": "c(\nperson(\"Barry\", \"Eggleston\", email = \"beggleston@rti.org\", role = c(\"cre\", \"aut\")),\nperson(\"Doug\", \"Wilson\", email = \"doug.roy.wilson@gmail.com\", role = c(\"aut\")),\nperson(\"Becky\", \"McNeil\", email = \"rmcneil@rti.org\", role = c(\"aut\")),\nperson(\"Joseph\", \"Ibrahim\", email = \"jibrahim@email.unc.edu\", role = c(\"aut\")),\nperson(\"Diane\", \"Catellier\", email = \"dcatellier@rti.org\", role = c(\"fnd\", \"rth\", \"aut\")))", "Description": "A set of functions to help clinical trial researchers\ncalculate power and sample size for two-arm Bayesian randomized\nclinical trials that do or do not incorporate historical\ncontrol data. At some point during the design process, a\nclinical trial researcher who is designing a basic two-arm\nBayesian randomized clinical trial needs to make decisions\nabout power and sample size within the context of hypothesized\ntreatment effects. Through simulation, the simple_sim()\nfunction will estimate power and other user specified clinical\ntrial characteristics at user specified sample sizes given user\ndefined scenarios about treatment effect,control group\ncharacteristics, and outcome. If the clinical trial researcher\nhas access to historical control data, then the researcher can\ndesign a two-arm Bayesian randomized clinical trial that\nincorporates the historical data. In such a case, the\nresearcher needs to work through the potential consequences of\nhistorical and randomized control differences on trial\ncharacteristics, in addition to working through issues\nregarding power in the context of sample size, treatment effect\nsize, and outcome. If a researcher designs a clinical trial\nthat will incorporate historical control data, the researcher\nneeds the randomized controls to be from the same population as\nthe historical controls. What if this is not the case when the\ndesigned trial is implemented? During the design phase, the\nresearcher needs to investigate the negative effects of\npossible historic/randomized control differences on power, type\none error, and other trial characteristics. Using this\ninformation, the researcher should design the trial to mitigate\nthese negative effects. Through simulation, the historic_sim()\nfunction will estimate power and other user specified clinical\ntrial characteristics at user specified sample sizes given user\ndefined scenarios about historical and randomized control\ndifferences as well as treatment effects and outcomes. The\nresults from historic_sim() and simple_sim() can be printed\nwith print_table() and graphed with plot_table() methods.\nOutcomes considered are Gaussian, Poisson, Bernoulli,\nLognormal, Weibull, and Piecewise Exponential. The methods are\ndescribed in Eggleston et al. (2021)\n.", "License": "GPL-3", "Encoding": "UTF-8", "URL": "https://github.com/begglest/BayesCTDesign", "BugReports": "https://github.com/begglest/BayesCTDesign/issues", "RoxygenNote": "7.1.2", "Config/pak/sysreqs": "libicu-dev", "Repository": "https://begglest.r-universe.dev", "Date/Publication": "2021-11-28 07:12:31 UTC", "RemoteUrl": "https://github.com/begglest/bayesctdesign", "RemoteRef": "HEAD", "RemoteSha": "1933631e5b749329a8b152b0d9c65022cb06993d", "NeedsCompilation": "no", "Packaged": { "Date": "2026-06-06 09:06:35 UTC", "User": "root" }, "Author": "Barry Eggleston [cre, aut],\nDoug Wilson [aut],\nBecky McNeil [aut],\nJoseph Ibrahim [aut],\nDiane Catellier [fnd, rth, aut]", "Maintainer": "Barry Eggleston ", "MD5sum": "8895d9fee9c31ef1ac8b38a5e670aea6", "_user": "begglest", "_type": "src", "_file": "BayesCTDesign_0.6.1.tar.gz", "_fileid": "54dcf6f5ed2075c6b0249d0c35dbf86b30e986ce4781d25fcdc0f1b2510f9d09", "_filesize": 239058, "_sha256": 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