{ "_id": "6a156a07acfb0bcc41d62d2a", "Package": "gestate", "Title": "Generalised Survival Trial Assessment Tool Environment", "Version": "1.6.0", "Authors@R": "c(\nperson(\"James\", \"Bell\", email = \"james.bell.ext@boehringer-ingelheim.com\", role = c(\"aut\", \"cre\")),\nperson(\"Jasmin\", \"Ruehl\", email = \"\",role = \"ctb\"))", "Description": "Provides tools to assist planning and monitoring of\ntime-to-event trials under complicated censoring assumptions\nand/or non-proportional hazards. There are three main\ncomponents: The first is analytic calculation of predicted\ntime-to-event trial properties, providing estimates of expected\nhazard ratio, event numbers and power under different analysis\nmethods. The second is simulation, allowing stochastic\nestimation of these same properties. Thirdly, it provides\nparametric event prediction using blinded trial data, including\ncreation of prediction intervals. Methods are based upon\nnumerical integration and a flexible object-orientated\nstructure for defining event, censoring and recruitment\ndistributions (Curves).", "License": "GPL-3", "Encoding": "UTF-8", "RoxygenNote": "7.1.1", "VignetteBuilder": "knitr", "NeedsCompilation": "no", "Packaged": { "Date": "2026-05-26 09:34:27 UTC", "User": "root" }, "Author": "James Bell [aut, cre], Jasmin Ruehl [ctb]", "Maintainer": "James Bell ", "Config/pak/sysreqs": "cmake make libuv1-dev zlib1g-dev", "Repository": "https://jamescbell.r-universe.dev", "Date/Publication": "2023-04-26 10:02:30 UTC", "RemoteUrl": "https://github.com/cran/gestate", "RemoteRef": "HEAD", "RemoteSha": "4eda0e9fcc7af2a82cb94f1aa643330244a8bb0c", "MD5sum": "3c22de1e31abcb8e97c53d8142140015", "_user": "jamescbell", "_type": "src", "_file": "gestate_1.6.0.tar.gz", "_fileid": "92a0373560e72691c1f8cb57161088b667453c9c34b6d13140e79aa1dac76b04", "_filesize": 1231256, "_sha256": 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"shiny", "role": "Imports" }, { "package": "shinythemes", "role": "Imports" }, { "package": "survival", "role": "Imports" }, { "package": "methods", "role": "Imports" }, { "package": "testthat", "role": "Suggests" }, { "package": "knitr", "role": "Suggests" }, { "package": "rmarkdown", "role": "Suggests" } ], "_owner": "cran", "_selfowned": true, "_usedby": 0, "_updates": [], "_tags": [], "_stars": 2, "_contributors": [ { "user": "jamescbell", "count": 4, "uuid": 83281256 } ], "_userbio": { "uuid": 83281256, "type": "user", "name": "JamesCBell" }, "_downloads": { "count": 209, "source": "https://cranlogs.r-pkg.org/downloads/total/last-month/gestate" }, "_searchresults": 8, "_rbuild": "4.6.0", "_assets": [ "extra/citation.cff", "extra/citation.html", "extra/citation.json", "extra/citation.txt", "extra/contents.json", "extra/gestate.html", "manual.pdf" ], "_realowner": "jamescbell", "_cranurl": false, "_releases": [ { "version": "1.3.2", "date": "2019-04-26" }, { "version": "1.4.0", "date": "2020-02-20" }, { "version": "1.5.0", "date": "2021-11-24" }, { "version": "1.6.0", "date": "2023-04-26" } ], "_exports": [ "analyse_sim", "Blank", "create_tte_prior", "createRFfunction", "evaluateCDFfunction", "evaluateInvfunction", "evaluatePDFfunction", "event_prediction", "event_prediction_KM", "event_prediction_prior", "Exponential", "fit_KM", "fit_tte_data", "fit_tte_data_prior", "frontierpower", "getAssessCDFfunction", "getCDFfunction", "getInvfunction", "getLength", "getMaxF", "getN", "getNactive", "getNames", "getNcontrol", "getParam", "getParams", "getParamsV", "getPatients", "getPDFfunction", "getRatio", "getRFfunction", "getType", "GGamma", "Gompertz", "InstantR", "LinearR", "LogLogistic", "Lognormal", "MixExp", "MixWei", "nph_traj", "PieceExponential", "PieceR", "PieceRMaxF", "plot_ep", "plot_km_fit", "plot_npht", "plotCDF", "plotRecruitment", "plotSF", "random_draw", "run_gestate", "set_assess_time", "set_event_number", "setPatients", "show", "simulate_trials", "simulate_trials_strata", "summarise_analysis", "survfit_fast", "Weibull" ], "_help": [ { "page": "analyse_sim", "title": "Analyse simulations of time-to-event data using arbitrary event, censoring and recruitment distributions.", "topics": [ "analyse_sim" ] }, { "page": "Blank", "title": "Blank Curve constructor function", "topics": [ "Blank" ] }, { "page": "create_tte_prior", "title": "Create an arbitrary prior data set from a specified Curve object", "topics": [ "create_tte_prior" ] }, { "page": "createRFfunction", "title": "Method for creating a random draw function from a Curve object", "topics": [ "createRFfunction" ] }, { "page": "createRFfunction-Curve-method", "title": "Method for creating a random draw function from a Curve object", "topics": [ "createRFfunction,Curve-method" ] }, { "page": "Curve-class", "title": "Curve Class for defining distributions", "topics": [ "Curve-class" ] }, { "page": "evaluateCDFfunction", "title": "Method for evaluating the CDF function for a Curve object at q", "topics": [ "evaluateCDFfunction" ] }, { "page": "evaluateCDFfunction-Curve-method", "title": "Method for evaluating the CDF function for a Curve object at q", "topics": [ "evaluateCDFfunction,Curve-method" ] }, { "page": "evaluateInvfunction", "title": "Method for evaluating the inverse-CDF function for a Curve object at p", "topics": [ "evaluateInvfunction" ] }, { "page": "evaluateInvfunction-Curve-method", "title": "Method for evaluating the inverse-CDF function for a Curve object at p", "topics": [ "evaluateInvfunction,Curve-method" ] }, { "page": "evaluatePDFfunction", "title": "Method for evaluating the PDF function for a Curve object at x", "topics": [ "evaluatePDFfunction" ] }, { "page": "evaluatePDFfunction-Curve-method", "title": "Method for evaluating the PDF function for a Curve object at x", "topics": [ "evaluatePDFfunction,Curve-method" ] }, { "page": "event_prediction", "title": "Event prediction using patient-level survival data and a recruitment RCurve", "topics": [ "event_prediction" ] }, { "page": "event_prediction_KM", "title": "Event prediction using a lifetable and a recruitment RCurve", "topics": [ "event_prediction_KM" ] }, { "page": "event_prediction_prior", "title": "Event prediction using patient-level survival data, prior data and a recruitment RCurve", "topics": [ "event_prediction_prior" ] }, { "page": "Exponential", "title": "Exponential Curve constructor function", "topics": [ "Exponential" ] }, { "page": "fit_KM", "title": "Fit Weibull, Log-Normal or Exponential survival curves to Kaplan Meier estimates", "topics": [ "fit_KM" ] }, { "page": "fit_tte_data", "title": "Fit Weibull, Log-Normal or Exponential survival curves to patient-level time-to-event data", "topics": [ "fit_tte_data" ] }, { "page": "fit_tte_data_prior", "title": "Fit Weibull survival curves to patient-level time-to-event data by including patient-level weighted prior data", "topics": [ "fit_tte_data_prior" ] }, { "page": "frontierpower", "title": "Calculate Frontier power from number of events", "topics": [ "frontierpower" ] }, { "page": "getAssessCDFfunction", "title": "Method for returning the CDF function for a RCurve object", "topics": [ "getAssessCDFfunction" ] }, { "page": "getAssessCDFfunction-RCurve-method", "title": "Method for returning the CDF function for a RCurve object", "topics": [ "getAssessCDFfunction,RCurve-method" ] }, { "page": "getCDFfunction", "title": "Method for returning the CDF function for a Curve object", "topics": [ "getCDFfunction" ] }, { "page": "getCDFfunction-Curve-method", "title": "Method for returning the CDF function for a Curve object", "topics": [ "getCDFfunction,Curve-method" ] }, { "page": "getInvfunction", "title": "Method for returning the inverse-CDF function for a Curve object", "topics": [ "getInvfunction" ] }, { "page": "getInvfunction-Curve-method", "title": "Method for returning the inverse-CDF function for a Curve object", "topics": [ "getInvfunction,Curve-method" ] }, { "page": "getLength", "title": "Method for returning the recruitment length from a RCurve", "topics": [ "getLength" ] }, { "page": "getLength-RCurve-method", "title": "Method for returning the recruitment length from a RCurve", "topics": [ "getLength,RCurve-method" ] }, { "page": "getMaxF", "title": "Method for returning maximum duration of patient follow-up from a RCurve", "topics": [ "getMaxF" ] }, { "page": "getMaxF-RCurve-method", "title": "Method for returning maximum duration of patient follow-up from a RCurve", "topics": [ "getMaxF,RCurve-method" ] }, { "page": "getN", "title": "Method for returning the total patient number from a RCurve", "topics": [ "getN" ] }, { "page": "getN-RCurve-method", "title": "Method for returning the total patient number from a RCurve", "topics": [ "getN,RCurve-method" ] }, { "page": "getNactive", "title": "Method for returning the active arm patient number from a RCurve", "topics": [ "getNactive" ] }, { "page": "getNactive-RCurve-method", "title": "Method for returning the active arm patient number from a RCurve", "topics": [ "getNactive,RCurve-method" ] }, { "page": "getNames", "title": "Method for returning all parameter names from a Curve object", "topics": [ "getNames" ] }, { "page": "getNames-Curve-method", "title": "Method for returning all parameter names from a Curve object", "topics": [ "getNames,Curve-method" ] }, { "page": "getNcontrol", "title": "Method for returning the control arm patient number from a RCurve", "topics": [ "getNcontrol" ] }, { "page": "getNcontrol-RCurve-method", "title": "Method for returning the control arm patient number from a RCurve", "topics": [ "getNcontrol,RCurve-method" ] }, { "page": "getParam", "title": "Method for returning a single parameter from a Curve object", "topics": [ "getParam" ] }, { "page": "getParam-Curve-method", "title": "Method for returning a single parameter from a Curve object", "topics": [ "getParam,Curve-method" ] }, { "page": "getParams", "title": "Method for returning all parameters from a Curve object as a list", "topics": [ "getParams" ] }, { "page": "getParams-Curve-method", "title": "Method for returning all parameters from a Curve object as a list", "topics": [ "getParams,Curve-method" ] }, { "page": "getParamsV", "title": "Method for returning all parameters from a Curve object as a vector", "topics": [ "getParamsV" ] }, { "page": "getParamsV-Curve-method", "title": "Method for returning all parameters from a Curve object as a vector", "topics": [ "getParamsV,Curve-method" ] }, { "page": "getPatients", "title": "Method for calculating expected number of recruited patients at a given time from an RCurve", "topics": [ "getPatients" ] }, { "page": "getPatients-RCurve-method", "title": "Method for calculating expected number of recruited patients at a given time from an RCurve", "topics": [ "getPatients,RCurve-method" ] }, { "page": "getPDFfunction", "title": "Method for returning the PDF function for a Curve object", "topics": [ "getPDFfunction" ] }, { "page": "getPDFfunction-Curve-method", "title": "Method for returning the PDF function for a Curve object", "topics": [ "getPDFfunction,Curve-method" ] }, { "page": "getRatio", "title": "Method for returning the recruitment ratio from a RCurve", "topics": [ "getRatio" ] }, { "page": "getRatio-RCurve-method", "title": "Method for returning the recruitment ratio from a RCurve", "topics": [ "getRatio,RCurve-method" ] }, { "page": "getRFfunction", "title": "Method for returning the RF function for a Curve object", "topics": [ "getRFfunction" ] }, { "page": "getRFfunction-Curve-method", "title": "Method for returning the RF function for a Curve object", "topics": [ "getRFfunction,Curve-method" ] }, { "page": "getType", "title": "Method for returning the Curve type", "topics": [ "getType" ] }, { "page": "getType-Curve-method", "title": "Method for returning the Curve type", "topics": [ "getType,Curve-method" ] }, { "page": "GGamma", "title": "Generalised Gamma Curve constructor function", "topics": [ "GGamma" ] }, { "page": "Gompertz", "title": "Gompertz Curve constructor function", "topics": [ "Gompertz" ] }, { "page": "InstantR", "title": "InstantR RCurve constructor function", "topics": [ "InstantR" ] }, { "page": "LinearR", "title": "LinearR RCurve constructor function", "topics": [ "LinearR" ] }, { "page": "LogLogistic", "title": "Log-logistic Curve constructor function", "topics": [ "LogLogistic" ] }, { "page": "Lognormal", "title": "Log-normal Curve constructor function", "topics": [ "Lognormal" ] }, { "page": "MixExp", "title": "Mixture Exponential Curve constructor function", "topics": [ "MixExp" ] }, { "page": "MixWei", "title": "Mixture Weibull Curve constructor function", "topics": [ "MixWei" ] }, { "page": "nph_traj", "title": "Calculate analytic time-to-event trial properties under non-proportional hazards and complex assumptions", "topics": [ "nph_traj" ] }, { "page": "PieceExponential", "title": "Piecewise Exponential Curve constructor function", "topics": [ "PieceExponential" ] }, { "page": "PieceR", "title": "PieceR RCurve constructor function", "topics": [ "PieceR" ] }, { "page": "PieceRMaxF", "title": "PieceR RCurve constructor function", "topics": [ "PieceRMaxF" ] }, { "page": "plot_ep", "title": "Plot event prediction output", "topics": [ "plot_ep" ] }, { "page": "plot_km_fit", "title": "Kaplan Meier Plot of Curve-Fit", "topics": [ "plot_km_fit" ] }, { "page": "plot_npht", "title": "Plot output from nph_traj", "topics": [ "plot_npht" ] }, { "page": "plotCDF", "title": "Method for plotting the CDF of a Curve object", "topics": [ "plotCDF" ] }, { "page": "plotCDF-Curve-method", "title": "Method for plotting the CDF of a Curve object", "topics": [ "plotCDF,Curve-method" ] }, { "page": "plotRecruitment", "title": "Method for plotting the Recruitment Function of a RCurve object", "topics": [ "plotRecruitment" ] }, { "page": "plotRecruitment-RCurve-method", "title": "Method for plotting the Recruitment Function of a RCurve object", "topics": [ "plotRecruitment,RCurve-method" ] }, { "page": "plotSF", "title": "Method for plotting the Survival Function of a Curve object", "topics": [ "plotSF" ] }, { "page": "plotSF-Curve-method", "title": "Method for plotting the Survival Function of a Curve object", "topics": [ "plotSF,Curve-method" ] }, { "page": "random_draw", "title": "Method for taking random draws from a Curve object distribution", "topics": [ "random_draw" ] }, { "page": "random_draw-Curve-method", "title": "Method for taking random draws from a Curve object distribution", "topics": [ "random_draw,Curve-method" ] }, { "page": "RCurve-class", "title": "RCurve Class for defining recruitment distributions", "topics": [ "RCurve-class" ] }, { "page": "run_gestate", "title": "Load Shiny for Gestate Loads the Shiny interactive GUI for gestate", "topics": [ "run_gestate" ] }, { "page": "set_assess_time", "title": "Adjusts assessment time for simulations", "topics": [ "set_assess_time" ] }, { "page": "set_event_number", "title": "Adjusts simulations so that administrative censoring occurs at a fixed event number, rather than a fixed time", "topics": [ "set_event_number" ] }, { "page": "setPatients", "title": "Method for setting N's in an RCurve", "topics": [ "setPatients" ] }, { "page": "setPatients-RCurve-method", "title": "Method for setting N's in an RCurve", "topics": [ "setPatients,RCurve-method" ] }, { "page": "show-Curve-method", "title": "Method for displaying Curve objects neatly - replaces standard show method", "topics": [ "show,Curve-method" ] }, { "page": "show-RCurve-method", "title": "Method for displaying RCurve objects neatly - replaces standard show method", "topics": [ "show,RCurve-method" ] }, { "page": "simulate_trials", "title": "Perform simulations of time-to-event data using arbitrary event, censoring and recruitment distributions.", "topics": [ "simulate_trials" ] }, { "page": "simulate_trials_strata", "title": "Perform multi-strata simulations 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event_prediction_prior", "4.4 Weibull Event Prediction with Weighted Prior Data Example" ], "created": "2019-04-26 07:20:04", "modified": "2023-04-26 10:02:30", "commits": 3 }, { "source": "trial_planning.Rmd", "filename": "trial_planning.html", "title": "Planning Time-To-Event Trials with gestate", "author": "James Bell", "engine": "knitr::rmarkdown", "headings": [ "1 Introduction", "1.1 Vignette Overview", "1.2 Exponential Distributions", "1.3 Non-Proportional Hazards and Complex Censoring", "1.4 Power Calculation vs Sample Size Calculation", "1.5 Shiny App", "2 Curves", "2.1 Event and Censoring Distribution Description and Storage: Curve Objects", "2.2 Recruitment distribution description and storage: RCurve", "3 Analytic Planning of Time-to-Event Trials: nph_traj", "3.1 Getting started: Simple Log-Rank and Hazard-Ratio Calculations", "3.2 Interpreting Output", "3.3 Censoring", "3.4 Other/Advanced Options", "3.5 Planning for Landmark and RMST Analysis", "3.6 Plotting nph_traj Output", "4 Simulating Trial Properties", "4.1 Simulating Data: simulate_trials", "4.2 Simulating Stratified Data: simulate_trials_strata", "4.3 Modifying Simulated Data: set_event_number and set_assess_time", "4.4 Analysing Simulated Data: analyse_sim", "4.5 Summarising Analysed Data: summarise_analysis", "4.6 Comparisons of Simulated Data to Analytic Outputs", "5 References" ], "created": "2019-04-26 07:20:04", "modified": "2023-04-26 10:02:30", "commits": 4 } ], "_score": 2.6020599913279625, "_indexed": true, "_nocasepkg": "gestate", "_universes": [ "jamescbell" ], "_binaries": [ { "r": "4.7.0", "os": "linux", "version": "1.6.0", "date": "2026-05-26T09:36:57.000Z", "distro": "noble", "commit": "4eda0e9fcc7af2a82cb94f1aa643330244a8bb0c", "fileid": "b0271c2dd04b72106f7fbf1933a8976d41ca1e89028fdd7f724b9394a66bde0d", "status": "success", "check": "NOTE", "buildurl": "https://github.com/r-universe/jamescbell/actions/runs/26444212114" }, { "r": "4.6.0", "os": "linux", "version": "1.6.0", 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