Object-Oriented Implementation of Dose Escalation Designs
Logical AND Operator for Opening Objects
Combine Two Stopping Rules with AND
Combine an Atomic Stopping Rule and a Stopping List with AND
Combine a Stopping List and an Atomic Stopping Rule with AND
CohortSizeParts
CohortSizeRandom
CohortSizeRange
DASimulations
Helper function to calculate percentage of true stopping rules for rep...
Checking Formals of a Function
Convert a Ordinal Data to the Equivalent Binary Data for a Specific Gr...
Convert an ordinal CRM model to the Equivalent Binary CRM Model for a ...
Convert a Samples Object from an ordinal Model to the Equivalent Sampl...
Building the Plot for nextBest-NextBestMaxGainSamples Method.
Target Function for Quantiles Optimization
Combining S4 Class Validation Results
Helper Function performing validation Common to Data and DataOrdinal
Increments
IncrementsRelative
"MAX" Combination of Cohort Size Rules
Obtaining Posterior Samples for all Model Parameters
McmcOptions
Construct a Minimally Informative Prior
"MIN" Combination of Cohort Size Rules
NextBest
Finding the Next Best Dose
NextBestMinDist
NextBestMTD
SafetyWindowConst
StoppingMTDdistribution
StoppingOrdinal
Internal Helper Functions for Validation of GeneralModel and `ModelP...
Internal Helper Functions for Validation of Model Parameters Objects
Internal Helper Functions for Validation of NextBest Objects
Internal Helper Functions for Validation of Opening Objects
Helper Function to Blind Plot Data
Helper Function to Create Doses Tried Plot
The Names of the Sampled Parameters
Helper Function to Create Trajectory Plot
Approximate posterior with (log) normal distribution
Additional Assertions for checkmate
Backfill class
Get the Biomarker Levels for a Given Dual-Endpoint Model, Given Dose L...
Check if All Arguments Are Equal
Check That Labels Are Valid and Useful
Check that an argument is a valid format specification
Check if vectors are of compatible lengths
Check if an argument is a probability vector
Check if an argument is a probability range
Check if an argument is a single probability value
Append Units to a Numeric Dose
Check that an argument is a numerical range
CohortSize
CohortSizeConst
CohortSizeDLT
CohortSizeMax
CohortSizeMin
CohortSizeOrdinal
Object-oriented implementation of CRM designs
CrmPackClass
Open the Example PDF for crmPack
Open the Browser with Help Pages for crmPack
DADesign
DALogisticLogNormal
Apply a Function to Subsets of Data Frame.
Data
DataDA
DataDual
DataGrouped
DataMixture
Helper Function to Calculate Fit Summary
DataOrdinal
DataParts
Design
DesignGrouped
DesignOrdinal
Compute the Density of Inverse Gamma Distribution
Likelihood of DLTs in each interval
DualEndpointEmax
Getting the Dose Grid Range
Computing the Doses for a given independent variable, Model and Sample...
Getting the Dose Function for a Given Model Type
DualDesign
DualEndpoint
DualEndpointBeta
DualEndpointRW
DualResponsesDesign.R
DualResponsesSamplesDesign
DualSimulations
DualSimulationsSummary
GeneralModel
EffFlexi
Computing Expected Efficacy for a Given Dose, Model and Samples
Getting the Efficacy Function for a Given Model Type
Effloglog
Verbose Logging
Obtain Hypothetical Trial Course Table for a Design
Fit method for the Samples class
Convenience function to make barplots of percentages
Get the fitted values for the gain values at all dose levels based on ...
Get the fitted DLT free survival (piecewise exponential model). This f...
FractionalCRM
Compute Gain Values based on Pseudo DLE and a Pseudo Efficacy Models a...
GeneralData
GeneralSimulations
GeneralSimulationsSummary
Helper Function to Obtain Simulation Results List
Get specific parameter samples and produce a data.frame
Extracting Efficacy Responses for Subjects Categorized by the DLT
Comparison with Numerical Tolerance and Without Name Comparison
Helpers for stripping expressions of covr-inserted trace code
Getting the default value for an empty object
Helper function to determine the dlts including first separate and pla...
Helper Function to Enroll Backfill Patients
Find Interval Numbers or Indices and Return Custom Number For 0.
Helper Function to Calculate Inverse Dose
Conditional Formatting Using C-style Formats
Format a doseGrid for Printing
Helper for Minimal Informative Unimodal Beta Distribution
Get Starting Values for Quantiles Optimization
Group Together Mono and Combo Data
Check which elements are in a given range
Calculating the Information Theoretic Distance
Shorthand for Logit Function
Testing Matrix for Positive Definiteness
Appending a Dummy Number for Selected Slots in Data
Extracting Samples from JAGS mcarray Object
Getting Data for JAGS
Setting Initial Values for JAGS Model Parameters
Joining JAGS Models
Writing JAGS Model to a File
Set Default Values for kable Parameters
Used to obtain expected format.
Update certain components of DualEndpoint model with regard to param...
Update DualEndpoint class model components with regard to DLT and bi...
Update certain components of DualEndpoint model with regard to prior...
Update DualEndpoint class model components with regard to biomarker ...
Get Eligible Doses from the Dose Grid.
Credibility Intervals for Max Gain and Target Doses at `nextBest-NextB...
Get Closest Grid Doses for a Given Target Doses for `nextBest-NextBest...
Building the Plot for nextBest-NextBestMaxGain Method.
Building the Plot for nextBest-NextBestNCRMLoss Method.
Building the Plot for nextBest-NextBestTD Method.
Building the Plot for nextBest-NextBestTDsamples Method.
Getting NULL for NA
Helper Function Containing Common Functionality
Preparing Cohort Lines for Data Plot
Preparing Data for Plotting
Recursively Apply a Function to a List
Helper Function to create return list for Simulations output
Getting the Slots from a S4 Object
Helper function to calculate average across iterations for each additi...
Check that an argument is a named vector of type numeric
Helper Function to call truth calculation
Helper function to recursively unpack stopping rules and return lists ...
Helper Function to Update Backfill Queue
IncrementsDoseLevels
IncrementsHSRBeta
IncrementsMaxToxProb
IncrementsMin
IncrementsOrdinal
Helper Function for Value Matching with Tolerance
IncrementsRelativeDLT
IncrementsRelativeDLTCurrent
IncrementsRelativeParts
Render a CohortSizeConst Object
LogisticIndepBeta
Determine the Maximum Possible Next Dose
LogisticKadane
LogisticKadaneBetaGamma
LogisticLogNormal
LogisticLogNormalGrouped
Calculate Maximum Number of Backfill Patients
LogisticLogNormalMixture
LogisticLogNormalOrdinal
LogisticLogNormalSub
LogisticNormal
LogisticNormalFixedMixture
LogisticNormalMixture
ModelEff
ModelLogNormal
ModelParamsNormal
ModelPseudo
ModelTox
MCMC Sampling for Bayesian Logistic Regression Model
NextBestDualEndpoint
NextBestEWOC
NextBestInfTheory
NextBestMaxGain
NextBestMaxGainSamples
NextBestNCRM
NextBestNCRMLoss
NextBestOrdinal
NextBestProbMTDLTE
NextBestProbMTDMinDist
NextBestTD
NextBestTDsamples
NextBestThreePlusThree
Number of Doses in Grid
OneParExpPrior
OpeningMinDose
OneParLogNormalPrior
Open / recruit backfill patients into a cohort?
Opening
OpeningAll
OpeningAny
OpeningList
OpeningMinCohorts
Plot Dual-Endpoint Design Simulation Summary
OpeningMinResponses
OpeningNone
Logical OR Operator for Opening Objects
Combine Two Stopping Rules with OR
Combine an Atomic Stopping Rule and a Stopping List with OR
Combine a Stopping List and an Atomic Stopping Rule with OR
Compute the Distribution Function of Inverse Gamma Distribution
Pipe operator
Plot GeneralSimulations
Plot of the fitted dose-tox based with a given pseudo DLE model and da...
Helper Function for the Plot Method of the Data and DataOrdinal Classe...
Plot Method for the DataDA Class
Plot Method for the DataDual Class
Plot of the fitted dose-efficacy based with a given pseudo efficacy mo...
Plot DualSimulations
Plot GeneralSimulationsSummary
Plot PseudoDualFlexiSimulations
Plot PseudoDualSimulations
Plot PseudoDualSimulationsSummary
Plot PseudoSimulationsSummary
Plotting dose-toxicity model fits
Plotting dose-toxicity and dose-biomarker model fits
Plotting dose-toxicity model fits
Plot the fitted dose-efficacy curve using a model from ModelEff clas...
Plot the fitted dose-DLE curve using a ModelTox class model with sam...
Plot Model-Based Design Simulation Summary
Plot gtable Objects
Plot of the DLE and efficacy curve side by side given a DLE pseudo mod...
Compute the Quantile Function of Inverse Gamma Distribution
Plot the gain curve in addition with the dose-DLE and dose-efficacy cu...
positive_number
Print Vignette
Computing Toxicity Probabilities for a Given Dose, Model and Samples
Getting the Prob Function for a Given Model Type
Shorthand for Probit Function
ProbitLogNormal
SafetyWindow
ProbitLogNormalRel
PseudoDualFlexiSimulations
PseudoDualSimulations
PseudoDualSimulationsSummary
PseudoSimulations
PseudoSimulationsSummary
Convert Prior Quantiles to Logistic (Log) Normal Model
Recruitment
RecruitmentRatio
RecruitmentUnlimited
Random Generation for the Inverse Gamma Distribution
RuleDesign
RuleDesignOrdinal
SafetyWindowSize
Samples
Determining if this Sample Should be Saved
Helper Function to Set and Save the RNG Seed
Show the Summary of Dual-Endpoint Simulations
Show Simulations Objects
Show the Summary of the Simulations
Show the Summary of PseudoDualSimulations
Show the Summary of PseudoSimulations
Show the Summary of Model-Based Design Simulations
Simulate outcomes from a time-to-DLT augmented CRM design
Simulate outcomes from a CRM design
Simulate Method for the DesignGrouped Class
Simulate outcomes from a dual-endpoint design
Simulate dose escalation procedure using both DLE and efficacy respons...
Simulate dose escalation procedure using DLE and efficacy responses wi...
Stop the trial?
Simulate outcomes from a rule-based design
Simulate dose escalation procedure using DLE responses only without sa...
Simulate dose escalation procedure using DLE responses only with DLE s...
Simulations
SimulationsSummary
Size of an Object
StartingDose
Stopping
Subsetting Operator for the Data Class
StoppingAll
StoppingAny
StoppingCohortsNearDose
StoppingExternal
StoppingHighestDose
StoppingList
StoppingLowestDoseHSRBeta
StoppingMaxGainCIRatio
StoppingMinCohorts
StoppingMinPatients
StoppingMissingDose
StoppingMTDCV
StoppingPatientsNearDose
StoppingSpecificDose
StoppingTargetBiomarker
StoppingTargetProb
StoppingTDCIRatio
Summarize Dual-Endpoint Design Simulations
Summarize the GeneralSimulations, Relative to a Given Truth
Summarize PseudoDualFlexiSimulations
Summarize PseudoDualSimulations
Summarize PseudoSimulations
Summarize Model-Based Design Simulations
Internal Helper Functions for Validation of McmcOptions Objects
TDDesign
TDsamplesDesign
Tidying CrmPackClass objects
TITELogisticLogNormal
Internal Helper Functions for Validation of GeneralSimulations Objec...
Updating Data Objects
Updating DataDA Objects
Updating DataDual Objects
Updating DataOrdinal Objects
Updating DataParts Objects
Update method for the ModelPseudo model class. This is a method to u...
Internal Helper Functions for Validation of Backfill Objects
Internal Helper Functions for Validation of CohortSize Objects
Internal Helper Functions for Validation of GeneralData Objects
Internal Helper Functions for Validation of RuleDesign Objects
Internal Helper Functions for Validation of Increments Objects
Internal Helper Functions for Validation of PseudoSimulations Object...
Internal Helper Functions for Validation of Recruitment Objects
Internal Helper Functions for Validation of SafetyWindow Objects
Internal Helper Functions for Validation of Samples Objects
Internal Helper Functions for Validation of StartingDose Objects
Internal Helper Functions for Validation of Stopping Objects
Validate
Determine the Safety Window Length of the Next Cohort
Implements a wide range of dose escalation designs. The focus is on model-based 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. Bayesian inference is performed via MCMC sampling in JAGS, and it is easy to setup a new design with custom 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. Further details are presented in Sabanés Bové et al. (2019) <doi:10.18637/jss.v089.i10>.
Useful links