- Home
- CRAN
**crmPack**: Object-Oriented Implementation of CRM Designs**TDsamplesDesign**: Initialization function for 'TDsamplesDesign' class

# Initialization function for 'TDsamplesDesign' class

### Description

Initialization function for 'TDsamplesDesign' class

### Usage

1 2 | ```
TDsamplesDesign(model, stopping, increments,
PLcohortSize = CohortSizeConst(1), ...)
``` |

### Arguments

`model` |
see |

`stopping` |
see |

`increments` |
see |

`PLcohortSize` |
see |

`...` |
additional arguments for |

### Value

the `TDsamplesDesign`

class object

Want to suggest features or report bugs for rdrr.io? Use the GitHub issue tracker.

- AllModels-class: Class for All models This is a class where all models...
- and-StoppingAll-Stopping-method: The method combining a stopping list and an atomic
- and-Stopping-StoppingAll-method: The method combining an atomic and a stopping list
- and-Stopping-Stopping-method: The method combining two atomic stopping rules
- approximate: Approximate posterior with (log) normal distribution
- as.list-GeneralData-method: as.list method for the "GeneralData" class
- biomLevel: Compute the biomarker level for a given dose, given model and...
- CohortSize-class: The virtual class for cohort sizes
- CohortSizeConst: Initialization function for "CohortSizeConst"
- CohortSizeConst-class: Constant cohort size
- CohortSizeDLT: Initialization function for "CohortSizeDLT"
- CohortSizeDLT-class: Cohort size based on number of DLTs
- CohortSizeMax: Initialization function for "CohortSizeMax"
- CohortSizeMax-class: Size based on maximum of multiple cohort size rules
- CohortSizeMin: Initialization function for "CohortSizeMin"
- CohortSizeMin-class: Size based on minimum of multiple cohort size rules
- CohortSizeParts: Initialization function for "CohortSizeParts"
- CohortSizeParts-class: Cohort size based on the parts
- CohortSizeRange: Initialization function for "CohortSizeRange"
- CohortSizeRange-class: Cohort size based on dose range
- crmPackExample: Open the example pdf for crmPack
- crmPackHelp: Open the browser with help pages for crmPack
- crmPack-package: Object-oriented implementation of CRM designs
- Data: Initialization function for the "Data" class
- Data-class: Class for the data input
- DataDual: Initialization function for the "DataDual" class
- DataDual-class: Class for the dual endpoint data input
- DataMixture: Initialization function for the "DataMixture" class
- DataMixture-class: Class for the data with mixture sharing
- DataParts: Initialization function for the "DataParts" class
- DataParts-class: Class for the data with two study parts
- Design: Initialization function for "Design"
- Design-class: Class for the CRM design
- dinvGamma: Compute the density of Inverse gamma distribution
- dose: Compute the doses for a given probability, given model and...
- DualDesign: Initialization function for "DualDesign"
- DualDesign-class: Class for the dual-endpoint CRM design
- DualEndpoint: Initialization function for the "DualEndpoint" class
- DualEndpointBeta: Initialization function for the "DualEndpointBeta" class
- DualEndpointBeta-class: Dual endpoint model with beta function for dose-biomarker...
- DualEndpoint-class: General class for the dual endpoint model
- DualEndpointEmax: Initialization function for the "DualEndpointEmax" class
- DualEndpointEmax-class: Dual endpoint model with emax function for dose-biomarker...
- DualEndpointOld-class: Dual endpoint model
- DualEndpointRW: Initialization function for the "DualEndpointRW" class
- DualEndpointRW-class: Dual endpoint model with RW prior for biomarker
- DualResponsesDesign: Initialization function for 'DualResponsesDesign"
- DualResponsesDesign-class: This is a class of design based on DLE responses using the...
- DualResponsesSamplesDesign: Initialization function for 'DualResponsesSamplesDesign"
- DualResponsesSamplesDesign-class: This is a class of design based on DLE responses using the...
- DualSimulations: Initialization function for "DualSimulations"
- DualSimulations-class: Class for the simulations output from dual-endpoint model...
- DualSimulationsSummary-class: Class for the summary of dual-endpoint simulations output
- EffFlexi: Initialization function for the "EffFlexi" class
- EffFlexi-class: Class for the efficacy model in flexible form for prior...
- Effloglog: Initialization function for the "Effloglog" class
- Effloglog-class: Class for the linear log-log efficacy model using pseudo data...
- examine: Obtain hypothetical trial course table for a design
- ExpEff: Compute the expected efficacy based on a given dose, a given...
- fit: Fit method for the Samples class
- fitGain: Get the fiited values for the gain values at all dose levels...
- gain: Compute the gain value with a given dose level, given a...
- GeneralData-class: Class for general data input
- GeneralModel-class: No Intitialization function for this General class for model...
- GeneralSimulations: Initialization function for "GeneralSimulations"
- GeneralSimulations-class: General class for the simulations output
- GeneralSimulationsSummary-class: Class for the summary of general simulations output
- getEff: Extracting efficacy responses for subjects without or with a...
- getMinInfBeta: Get the minimal informative unimodal beta distribution
- getResultList: Helper function to obtain simulation results list
- get-Samples-character-method: Get specific parameter samples and produce a data.frame
- Increments-class: The virtual class for controlling increments
- IncrementsRelative: Initialization function for "IncrementsRelative"
- IncrementsRelative-class: Increments control based on relative differences in intervals
- IncrementsRelativeDLT: Initialization function for "IncrementsRelativeDLT"
- IncrementsRelativeDLT-class: Increments control based on relative differences in terms of...
- IncrementsRelativeParts: Initialization function for "IncrementsRelativeParts"
- IncrementsRelativeParts-class: Increments control based on relative differences in...
- initialize-DualEndpointOld-method: Initialization method for the "DualEndpointOld" class
- is.bool: Predicate checking for a boolean option
- is.probability: Predicate checking for a probability
- is.probRange: Predicate checking for a probability range
- is.scalar: Checking for scalar
- is.wholenumber: checks for whole numbers (integers)
- joinBodies: Helper function to join two function bodies
- joinModels: Helper function to join two BUGS models
- LogisticIndepBeta: Intialization function for "LogisticIndepBeta" class
- LogisticIndepBeta-class: No initialization function Standard logistic model with prior...
- LogisticKadane: Initialization function for the "LogisticKadane" class
- LogisticKadane-class: Reparametrized logistic model
- LogisticLogNormal: Initialization function for the "LogisticLogNormal" class
- LogisticLogNormal-class: Standard logistic model with bivariate (log) normal prior
- LogisticLogNormalMixture: Initialization function for the "LogisticLogNormalMixture"...
- LogisticLogNormalMixture-class: Standard logistic model with online mixture of two bivariate...
- LogisticLogNormalSub: Initialization function for the "LogisticLogNormalSub" class
- LogisticLogNormalSub-class: Standard logistic model with bivariate (log) normal prior...
- LogisticNormal: Initialization function for the "LogisticNormal" class
- LogisticNormal-class: Standard logistic model with bivariate normal prior
- LogisticNormalFixedMixture: Initialization function for the "LogisticNormalFixedMixture"...
- LogisticNormalFixedMixture-class: Standard logistic model with fixed mixture of multiple...
- LogisticNormalMixture: Initialization function for the "LogisticNormalMixture" class
- LogisticNormalMixture-class: Standard logistic model with flexible mixture of two...
- logit: Shorthand for logit function
- maxDose: Determine the maximum possible next dose
- maxSize: "MAX" combination of cohort size rules
- mcmc: Obtain posterior samples for all model parameters
- McmcOptions: Initialization function for the "McmcOptions" class
- McmcOptions-class: Class for the three canonical MCMC options
- MinimalInformative: Construct a minimally informative prior
- minSize: "MIN" combination of cohort size rules
- Model-class: Class for the model input
- ModelEff-class: No Initialization function class for Efficacy models using...
- ModelPseudo-class: Class of models using expressing their prior in form of...
- ModelTox-class: No intialization function Class for DLE models using pseudo...
- multiplot: Multiple plot function
- myBarplot: Convenience function to make barplots of percentages
- nextBest: Find the next best dose
- NextBest-class: The virtual class for finding next best dose
- NextBestDualEndpoint: Initialization function for "NextBestDualEndpoint"
- NextBestDualEndpoint-class: The class with the input for finding the next dose based on...
- NextBestMaxGain: Initialization function for the class 'NextBestMaxGain'
- NextBestMaxGain-class: Next best dose with maximum gain value based on a pseudo DLE...
- NextBestMaxGainSamples: Initialization function for class "NextBestMaxGainSamples"
- NextBestMaxGainSamples-class: Next best dose with maximum gain value based on a pseudo DLE...
- NextBestMTD: Initialization function for class "NextBestMTD"
- NextBestMTD-class: The class with the input for finding the next best MTD...
- NextBestNCRM: Initialization function for "NextBestNCRM"
- NextBestNCRM-class: The class with the input for finding the next dose in target...
- NextBestTD: Initialization function for the class "NextBestTD"
- NextBestTD-class: Next best dose based on Pseudo DLE model without sample
- NextBestTDsamples: Initialization function for class "NextBestTDsamples"
- NextBestTDsamples-class: Next best dose based on Pseudo DLE Model with samples
- NextBestThreePlusThree: Initialization function for "NextBestThreePlusThree"
- NextBestThreePlusThree-class: The class with the input for finding the next dose in target...
- noOverlap: Check overlap of two character vectors
- or-StoppingAny-Stopping: The method combining an atomic and a stopping list
- or-Stopping-Stopping: The method combining two atomic stopping rules
- or-Stopping-StoppingAny: The method combining a stopping list and an atomic
- pinvGamma: Compute the distribution function of Inverse gamma...
- plot-DataDual-missing-method: Plot method for the "DataDual" class
- plot-DataDual-ModelEff-method: Plot of the fitted dose-efficacy based with a given pseudo...
- plot-Data-missing-method: Plot method for the "Data" class
- plot-Data-ModelTox-method: Plot of the fitted dose-tox based with a given pseudo DLE...
- plotDualResponses: Plot of the DLE and efficacy curve side by side given a DLE...
- plot-DualSimulations-missing-method: Plot dual-endpoint simulations
- plot-DualSimulationsSummary-missing-method: Plot summaries of the dual-endpoint design simulations
- plotGain: Plot the gain curve in addition with the dose-DLE and...
- plot-GeneralSimulations-missing-method: Plot simulations
- plot-GeneralSimulationsSummary-missing-method: Graphical display of the general simulation summary
- plot.gtable: Plots gtable objects
- plot-PseudoDualFlexiSimulations-missing-method: This plot method can be applied to...
- plot-PseudoDualSimulations-missing-method: Plot simulations
- plot-PseudoDualSimulationsSummary-missing-method: Plot the summary of Pseudo Dual Simulations summary
- plot-PseudoSimulationsSummary-missing-method: Plot summaries of the pseudo simulations
- plot-Samples-DualEndpoint-method: Plotting dose-toxicity and dose-biomarker model fits
- plot-Samples-ModelEff-method: Plot the fitted dose-effcacy curve using a model from...
- plot-Samples-Model-method: Plotting dose-toxicity model fits
- plot-Samples-ModelTox-method: Plot the fitted dose-DLE curve using a 'ModelTox' class model...
- plot-SimulationsSummary-missing-method: Plot summaries of the model-based design simulations
- printVignette: Taken from utils package (print.vignette)
- prob: Compute the probability for a given dose, given model and...
- PseudoDualFlexiSimulations: Initialization function for 'PseudoDualFlexiSimulations'...
- PseudoDualFlexiSimulations-class: This is a class which captures the trial simulations design...
- PseudoDualSimulations: Initialization function for 'DualPseudoSimulations' class
- PseudoDualSimulations-class: This is a class which captures the trial simulations design...
- PseudoDualSimulationsSummary-class: Class for the summary of the dual responses simulations using...
- PseudoSimulations: Initialization function of the 'PseudoSimulations' class
- PseudoSimulations-class: This is a class which captures the trial simulations from...
- PseudoSimulationsSummary-class: Class for the summary of pseudo-models simulations output
- qinvGamma: Compute the quantile function of Inverse gamma distribution
- Quantiles2LogisticNormal: Convert prior quantiles (lower, median, upper) to logistic...
- Report: A Reference Class to represent sequentially updated reporting...
- rinvGamma: The random generation of the Inverse gamma distribution
- RuleDesign: Initialization function for "RuleDesign"
- RuleDesign-class: Class for rule-based designs
- safeInteger: Safe conversion to integer vector
- Samples: Initialization function for "Samples"
- Samples-class: Class for the MCMC output
- sampleSize: Compute the number of samples for a given MCMC options triple
- saveSample: Determine if we should save this sample
- setSeed: Helper function to set and save the RNG seed
- show-DualSimulationsSummary-method: Show the summary of the dual-endpoint simulations
- show-GeneralSimulationsSummary-method: Show the summary of the simulations
- show-PseudoDualSimulationsSummary-method: Show the summary of Pseudo Dual simulations summary
- show-PseudoSimulationsSummary-method: Show the summary of the simulations
- show-SimulationsSummary-method: Show the summary of the simulations
- simulate-Design-method: Simulate outcomes from a CRM design
- simulate-DualDesign-method: Simulate outcomes from a dual-endpoint design
- simulate-DualResponsesDesign-method: This is a methods to simulate dose escalation procedure using...
- simulate-DualResponsesSamplesDesign-method: This is a methods to simulate dose escalation procedure using...
- simulate-RuleDesign-method: Simulate outcomes from a rule-based design
- simulate-TDDesign-method: This is a methods to simulate dose escalation procedure only...
- simulate-TDsamplesDesign-method: This is a methods to simulate dose escalation procedure only...
- Simulations: Initialization function for the "Simulations" class
- Simulations-class: Class for the simulations output from model based designs
- SimulationsSummary-class: Class for the summary of model-based simulations output
- size: Determine the size of the next cohort
- StoppingAll: Initialization function for "StoppingAll"
- StoppingAll-class: Stop based on fullfillment of all multiple stopping rules
- StoppingAny: Initialization function for "StoppingAny"
- StoppingAny-class: Stop based on fullfillment of any stopping rule
- Stopping-class: The virtual class for stopping rules
- StoppingCohortsNearDose: Initialization function for "StoppingCohortsNearDose"
- StoppingCohortsNearDose-class: Stop based on number of cohorts near to next best dose
- StoppingGstarCIRatio: Initialization function for "StoppingGstarCIRatio"
- StoppingGstarCIRatio-class: Stop based on a target ratio, the ratio of the upper to the...
- StoppingHighestDose: Initialization function for "StoppingHighestDose"
- StoppingHighestDose-class: Stop when the highest dose is reached
- StoppingList: Initialization function for "StoppingList"
- StoppingList-class: Stop based on multiple stopping rules
- StoppingMinCohorts: Initialization function for "StoppingMinCohorts"
- StoppingMinCohorts-class: Stop based on minimum number of cohorts
- StoppingMinPatients: Initialization function for "StoppingMinPatients"
- StoppingMinPatients-class: Stop based on minimum number of patients
- StoppingMTDdistribution: Initialization function for "StoppingMTDdistribution"
- StoppingMTDdistribution-class: Stop based on MTD distribution
- StoppingPatientsNearDose: Initialization function for "StoppingPatientsNearDose"
- StoppingPatientsNearDose-class: Stop based on number of patients near to next best dose
- StoppingTargetBiomarker: Initialization function for "StoppingTargetBiomarker"
- StoppingTargetBiomarker-class: Stop based on probability of target biomarker
- StoppingTargetProb: Initialization function for "StoppingTargetProb"
- StoppingTargetProb-class: Stop based on probability of target tox interval
- StoppingTDCIRatio: Initialization function for "StoppingTDCIRatio"
- StoppingTDCIRatio-class: Stop based on a target ratio, the ratio of the upper to the...
- stopTrial: Stop the trial?
- summary-DualSimulations-method: Summarize the dual-endpoint design simulations, relative to...
- summary-GeneralSimulations-method: Summarize the simulations, relative to a given truth
- summary-PseudoDualFlexiSimulations-method: Summary for Pseudo Dual responses simulations given a pseudo...
- summary-PseudoDualSimulations-method: Summary for Pseudo Dual responses simulations, relative to a...
- summary-PseudoSimulations-method: Summarize the simulations, relative to a given truth
- summary-Simulations-method: Summarize the model-based design simulations, relative to a...
- TDDesign: Initialization function for 'TDDesign' class
- TDDesign-class: Design class using DLE responses only based on the pseudo DLE...
- TDsamplesDesign: Initialization function for 'TDsamplesDesign' class
- TDsamplesDesign-class: This is a class of design based only on DLE responses using...
- ThreePlusThreeDesign: Creates a new 3+3 design object from a dose grid
- update-DataDual-method: Update method for the "DataDual" class
- update-Data-method: Update method for the "Data" class
- update-DataParts-method: Update method for the "DataParts" class
- update-EffFlexi-method: Update method for the 'EffFlexi' Model class. This is a...
- update-Effloglog-method: Update method for the 'Effloglog' Model class. This is a...
- update-LogisticIndepBeta-method: Update method for the 'LogisticIndepBeta'Model class. This is...
- Validate: A Reference Class to help programming validation for new S4...
- writeModel: Creating a WinBUGS model file