Object-Oriented Implementation of CRM Designs
Dual endpoint model
No initialization function Standard logistic model with prior in form ...
Intialization function for "LogisticIndepBeta" class
Helper function for value matching with tolerance
The method combining a stopping list and an atomic
The method combining an atomic and a stopping list
Compute the distribution function of Inverse gamma distribution
Plot method for the "Data" class
Stop based on number of cohorts near to next best dose
Initialization function for "StoppingCohortsNearDose"
Stop based on number of patients near to next best dose
Initialization function for "StoppingPatientsNearDose"
Stop based on probability of target biomarker
Initialization function for "StoppingTargetBiomarker"
Stop based on probability of target tox interval
Initialization function for "StoppingTargetProb"
Update method for the "DataParts" class
Predicate checking for a probability
Predicate checking for a probability range
Predicate checking for a numeric range
Checking for scalar
checks for whole numbers (integers)
Helper function to join two function bodies
Helper function to join two BUGS models
The method combining a stopping list and an atomic
Initialization function for "CohortSizeMax"
Class for All models This is a class where all models inherit.
The method combining two atomic stopping rules
The method combining an atomic and a stopping list
Initialization function for the "DataDual" class
Approximate posterior with (log) normal distribution
as.list method for the "GeneralData" class
Compute the biomarker level for a given dose, given model and samples
The virtual class for cohort sizes
Constant cohort size
Initialization function for "CohortSizeConst"
Cohort size based on number of DLTs
Initialization function for "CohortSizeDLT"
Size based on maximum of multiple cohort size rules
Size based on minimum of multiple cohort size rules
Initialization function for "CohortSizeMin"
Cohort size based on the parts
Initialization function for "CohortSizeParts"
Cohort size based on dose range
Initialization function for "CohortSizeRange"
Object-oriented implementation of CRM designs
Open the example pdf for crmPack
Open the browser with help pages for crmPack
Class for the data input
Initialization function for the "Data" class
Class for the dual endpoint data input
Class for the data with mixture sharing
Initialization function for the "DataMixture" class
Class for the data with two study parts
Initialization function for the "DataParts" class
Class for the CRM design
Initialization function for "Design"
Compute the density of Inverse gamma distribution
Compute the doses for a given probability, given model and samples
Initialization function for "DualSimulations"
Class for the dual-endpoint CRM design
Initialization function for "DualDesign"
General class for the dual endpoint model
Initialization function for the "DualEndpoint" class
Dual endpoint model with beta function for dose-biomarker relationship
Initialization function for the "DualEndpointBeta" class
Dual endpoint model with emax function for dose-biomarker relationship
Initialization function for the "DualEndpointEmax" class
Class for the summary of dual-endpoint simulations output
Dual endpoint model with RW prior for biomarker
Initialization function for the "DualEndpointRW" class
This is a class of design based on DLE responses using the `LogisticIn...
Initialization function for 'DualResponsesDesign"
This is a class of design based on DLE responses using the `LogisticIn...
Initialization function for 'DualResponsesSamplesDesign"
Class for the simulations output from dual-endpoint model based design...
Class for the efficacy model in flexible form for prior expressed in f...
Initialization function for the "EffFlexi" class
Class for the linear log-log efficacy model using pseudo data prior
Initialization function for the "Effloglog" class
Obtain hypothetical trial course table for a design
Compute the expected efficacy based on a given dose, a given pseudo Ef...
Fit method for the Samples class
Initialization function for "IncrementsNumDoseLevels"
Get the fiited values for the gain values at all dose levels based on ...
Compute the gain value with a given dose level, given a pseudo DLE mod...
Class for general data input
No Intitialization function for this General class for model input
General class for the simulations output
Initialization function for "GeneralSimulations"
Class for the summary of general simulations output
Get specific parameter samples and produce a data.frame
Extracting efficacy responses for subjects without or with a DLE. This...
Get the minimal informative unimodal beta distribution
Helper function to obtain simulation results list
Max increment based on minimum of multiple increment rules
Initialization function for "IncrementMin"
The virtual class for controlling increments
Increments control based on number of dose levels
Increments control based on relative differences in intervals
Initialization function for "IncrementsRelative"
Increments control based on relative differences in terms of DLTs
Initialization function for "IncrementsRelativeDLT"
Increments control based on relative differences in intervals, with sp...
Initialization function for "IncrementsRelativeParts"
Initialization method for the "DualEndpointOld" class
Predicate checking for a boolean option
Reparametrized logistic model
Initialization function for the "LogisticKadane" class
Standard logistic model with bivariate (log) normal prior
Initialization function for the "LogisticLogNormal" class
Standard logistic model with online mixture of two bivariate log norma...
Initialization function for the "LogisticLogNormalMixture" class
Standard logistic model with bivariate (log) normal prior with substra...
Initialization function for the "LogisticLogNormalSub" class
Standard logistic model with bivariate normal prior
Initialization function for the "LogisticNormal" class
Standard logistic model with fixed mixture of multiple bivariate (log)...
Initialization function for the "LogisticNormalFixedMixture" class
Standard logistic model with flexible mixture of two bivariate normal ...
Initialization function for the "LogisticNormalMixture" class
Shorthand for logit function
The method combining two atomic stopping rules
Determine the maximum possible next dose
"MAX" combination of cohort size rules
Obtain posterior samples for all model parameters
Class for the three canonical MCMC options
Initialization function for the "McmcOptions" class
Construct a minimally informative prior
"MIN" combination of cohort size rules
Class for the model input
No Initialization function class for Efficacy models using pseudo data...
Class of models using expressing their prior in form of Pseudo data
No intialization function Class for DLE models using pseudo data prior...
Multiple plot function
Convenience function to make barplots of percentages
Do MCMC sampling for Bayesian logistic regression model
The virtual class for finding next best dose
Find the next best dose
The class with the input for finding the next best MTD estimate
The class with the input for finding the next dose based on the dual e...
Initialization function for "NextBestDualEndpoint"
Next best dose with maximum gain value based on a pseudo DLE and effic...
Initialization function for the class 'NextBestMaxGain'
Next best dose with maximum gain value based on a pseudo DLE and effic...
Initialization function for class "NextBestMaxGainSamples"
Initialization function for class "NextBestMTD"
The class with the input for finding the next dose in target interval
Initialization function for "NextBestNCRM"
Next best dose based on Pseudo DLE model without sample
Initialization function for the class "NextBestTD"
Next best dose based on Pseudo DLE Model with samples
Initialization function for class "NextBestTDsamples"
The class with the input for finding the next dose in target interval
Initialization function for "NextBestThreePlusThree"
Check overlap of two character vectors
Plot of the fitted dose-tox based with a given pseudo DLE model and da...
Plot method for the "DataDual" class
Plot of the fitted dose-efficacy based with a given pseudo efficacy mo...
Plot dual-endpoint simulations
Plot summaries of the dual-endpoint design simulations
Plot simulations
Compute the quantile function of Inverse gamma distribution
Graphical display of the general simulation summary
Plot for PseudoDualFlexiSimulations
Plot simulations
Plot the summary of Pseudo Dual Simulations summary
Plot summaries of the pseudo simulations
Plotting dose-toxicity and dose-biomarker model fits
Plotting dose-toxicity model fits
Class for the summary of pseudo-models simulations output
Plot the fitted dose-effcacy curve using a model from ModelEff class...
Plot the fitted dose-DLE curve using a ModelTox class model with sam...
Plot summaries of the model-based design simulations
Plots gtable objects
Plot of the DLE and efficacy curve side by side given a DLE pseudo mod...
Plot the gain curve in addition with the dose-DLE and dose-efficacy cu...
Taken from utils package (print.vignette)
Compute the probability for a given dose, given model and samples
Shorthand for probit function
Probit model with bivariate log normal prior
Initialization function for the "ProbitLogNormal" class
This is a class which captures the trial simulations design using both...
Initialization function for 'PseudoDualFlexiSimulations' class
This is a class which captures the trial simulations design using both...
Initialization function for 'DualPseudoSimulations' class
Class for the summary of the dual responses simulations using pseudo m...
This is a class which captures the trial simulations from designs usin...
Initialization function of the 'PseudoSimulations' class
Initialization function for "StoppingMTDdistribution"
Convert prior quantiles (lower, median, upper) to logistic (log) norma...
A Reference Class to represent sequentially updated reporting objects.
The random generation of the Inverse gamma distribution
Class for rule-based designs
Initialization function for "RuleDesign"
Safe conversion to integer vector
Class for the MCMC output
Initialization function for "Samples"
Compute the number of samples for a given MCMC options triple
Determine if we should save this sample
Helper function to set and save the RNG seed
Show the summary of the dual-endpoint simulations
Show the summary of the simulations
Show the summary of Pseudo Dual simulations summary
Show the summary of the simulations
Show the summary of the simulations
Simulate outcomes from a CRM design
Simulate outcomes from a dual-endpoint design
This is a methods to simulate dose escalation procedure using both DLE...
This is a methods to simulate dose escalation procedure using both DLE...
Simulate outcomes from a rule-based design
This is a methods to simulate dose escalation procedure only using the...
This is a methods to simulate dose escalation procedure only using the...
Class for the simulations output from model based designs
Initialization function for the "Simulations" class
Class for the summary of model-based simulations output
Determine the size of the next cohort
The virtual class for stopping rules
Stop based on fullfillment of all multiple stopping rules
Initialization function for "StoppingAll"
Stop based on fullfillment of any stopping rule
Initialization function for "StoppingAny"
Stop based on a target ratio, the ratio of the upper to the lower 95% ...
Initialization function for "StoppingGstarCIRatio"
Stop when the highest dose is reached
Initialization function for "StoppingHighestDose"
Stop based on multiple stopping rules
Initialization function for "StoppingList"
Stop based on minimum number of cohorts
Initialization function for "StoppingMinCohorts"
Stop based on minimum number of patients
Initialization function for "StoppingMinPatients"
Stop based on MTD distribution
Stop based on a target ratio, the ratio of the upper to the lower 95% ...
Initialization function for "StoppingTDCIRatio"
Stop the trial?
Summarize the dual-endpoint design simulations, relative to given true...
Summarize the simulations, relative to a given truth
Summary for Pseudo Dual responses simulations given a pseudo DLE model...
Summary for Pseudo Dual responses simulations, relative to a given pse...
Summarize the simulations, relative to a given truth
Summarize the model-based design simulations, relative to a given trut...
Design class using DLE responses only based on the pseudo DLE model wi...
Initialization function for 'TDDesign' class
This is a class of design based only on DLE responses using the 'Logis...
Initialization function for 'TDsamplesDesign' class
Creates a new 3+3 design object from a dose grid
Update method for the "Data" class
Update method for the "DataDual" class
Update method for the 'EffFlexi' Model class. This is a method to upda...
Update method for the 'Effloglog' Model class. This is a method to upd...
Update method for the 'LogisticIndepBeta'Model class. This is a method...
A Reference Class to help programming validation for new S4 classes
Creating a WinBUGS model file
Implements a wide range of model-based dose escalation designs, ranging from classical and modern continual reassessment methods (CRMs) based on dose-limiting toxicity endpoints to dual-endpoint designs taking into account a biomarker/efficacy outcome. The focus is on Bayesian inference, making it very easy to setup a new design with its own JAGS code. However, it is also possible to implement 3+3 designs for comparison or models with non-Bayesian estimation. The whole package is written in a modular form in the S4 class system, making it very flexible for adaptation to new models, escalation or stopping rules.