Object-Oriented Implementation of Dose Escalation Designs

---

Documentation for package ‘crmPack’ version 2.0.0

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

A B C D E F G H I K L M N O P Q R S T U V W misc

crmPack-package

Object-oriented implementation of CRM designs

-- A --

and-Stopping-Stopping	Combine Two Stopping Rules with AND
and-Stopping-StoppingAll	Combine an Atomic Stopping Rule and a Stopping List with AND
and-StoppingAll-Stopping	Combine a Stopping List and an Atomic Stopping Rule with AND
approximate	Approximate posterior with (log) normal distribution
approximate-method	Approximate posterior with (log) normal distribution
assertions	Additional Assertions for 'checkmate'
assert_equal	Check if All Arguments Are Equal
assert_format	Check that an argument is a valid format specification
assert_length	Check if vectors are of compatible lengths
assert_probabilities	Check if an argument is a probability vector
assert_probability	Check if an argument is a single probability value
assert_probability_range	Check if an argument is a probability range
assert_range	Check that an argument is a numerical range

-- B --

biomarker	Get the Biomarker Levels for a Given Dual-Endpoint Model, Given Dose Levels and Samples
biomarker-DualEndpoint	Get the Biomarker Levels for a Given Dual-Endpoint Model, Given Dose Levels and Samples
biomarker-method	Get the Biomarker Levels for a Given Dual-Endpoint Model, Given Dose Levels and Samples

-- C --

check_equal	Check if All Arguments Are Equal
check_format	Check that an argument is a valid format specification
check_length	Check if vectors are of compatible lengths
check_probabilities	Check if an argument is a probability vector
check_probability	Check if an argument is a single probability value
check_probability_range	Check if an argument is a probability range
check_range	Check that an argument is a numerical range
CohortSize	'CohortSize'
CohortSize-class	'CohortSize'
CohortSizeConst	'CohortSizeConst'
CohortSizeConst-class	'CohortSizeConst'
CohortSizeDLT	'CohortSizeDLT'
CohortSizeDLT-class	'CohortSizeDLT'
CohortSizeMax	'CohortSizeMax'
CohortSizeMax-class	'CohortSizeMax'
CohortSizeMin	'CohortSizeMin'
CohortSizeMin-class	'CohortSizeMin'
CohortSizeOrdinal	'CohortSizeOrdinal'
CohortSizeOrdinal-class	'CohortSizeOrdinal'
CohortSizeParts	'CohortSizeParts'
CohortSizeParts-class	'CohortSizeParts'
CohortSizeRange	'CohortSizeRange'
CohortSizeRange-class	'CohortSizeRange'
crmPack	Object-oriented implementation of CRM designs
CrmPackClass	'CrmPackClass'
CrmPackClass-class	'CrmPackClass'
crmPackExample	Open the Example PDF for crmPack
crmPackHelp	Open the Browser with Help Pages for crmPack

-- D --

DADesign	'DADesign'
DADesign-class	'DADesign'
DALogisticLogNormal	'DALogisticLogNormal'
DALogisticLogNormal-class	'DALogisticLogNormal'
dapply	Apply a Function to Subsets of Data Frame.
DASimulations	'DASimulations'
DASimulations-class	'DASimulations'
Data	'Data'
Data-class	'Data'
DataDA	'DataDA'
DataDA-class	'DataDA'
DataDual	'DataDual'
DataDual-class	'DataDual'
DataGrouped	'DataGrouped'
DataGrouped-class	'DataGrouped'
DataMixture	'DataMixture'
DataMixture-class	'DataMixture'
DataOrdinal	'DataOrdinal'
DataOrdinal-class	'DataOrdinal'
DataParts	'DataParts'
DataParts-class	'DataParts'
Design	'Design'
Design-class	'Design'
DesignGrouped	'DesignGrouped'
DesignGrouped-class	'DesignGrouped'
DesignOrdinal	'DesignOrdinal'
DesignOrdinal-class	'DesignOrdinal'
disable_logging	Verbose Logging
dose	Computing the Doses for a given independent variable, Model and Samples
dose-DualEndpoint	Computing the Doses for a given independent variable, Model and Samples
dose-EffFlexi	Computing the Doses for a given independent variable, Model and Samples
dose-Effloglog-noSamples	Computing the Doses for a given independent variable, Model and Samples
dose-LogisticIndepBeta	Computing the Doses for a given independent variable, Model and Samples
dose-LogisticIndepBeta-noSamples	Computing the Doses for a given independent variable, Model and Samples
dose-LogisticKadane	Computing the Doses for a given independent variable, Model and Samples
dose-LogisticKadaneBetaGamma	Computing the Doses for a given independent variable, Model and Samples
dose-LogisticLogNormal	Computing the Doses for a given independent variable, Model and Samples
dose-LogisticLogNormalGrouped	Computing the Doses for a given independent variable, Model and Samples
dose-LogisticLogNormalMixture	Computing the Doses for a given independent variable, Model and Samples
dose-LogisticLogNormalOrdinal	Computing the Doses for a given independent variable, Model and Samples
dose-LogisticLogNormalSub	Computing the Doses for a given independent variable, Model and Samples
dose-LogisticNormal	Computing the Doses for a given independent variable, Model and Samples
dose-LogisticNormalFixedMixture	Computing the Doses for a given independent variable, Model and Samples
dose-LogisticNormalMixture	Computing the Doses for a given independent variable, Model and Samples
dose-method	Computing the Doses for a given independent variable, Model and Samples
dose-OneParExpPrior	Computing the Doses for a given independent variable, Model and Samples
dose-OneParLogNormalPrior	Computing the Doses for a given independent variable, Model and Samples
dose-ProbitLogNormal	Computing the Doses for a given independent variable, Model and Samples
dose-ProbitLogNormalRel	Computing the Doses for a given independent variable, Model and Samples
doseFunction	Getting the Dose Function for a Given Model Type
doseFunction-GeneralModel	Getting the Dose Function for a Given Model Type
doseFunction-LogisticLogNormalOrdinal	Getting the Dose Function for a Given Model Type
doseFunction-method	Getting the Dose Function for a Given Model Type
doseFunction-ModelPseudo	Getting the Dose Function for a Given Model Type
dose_grid_range	Getting the Dose Grid Range
dose_grid_range-Data	Getting the Dose Grid Range
dose_grid_range-method	Getting the Dose Grid Range
DualDesign	'DualDesign'
DualDesign-class	'DualDesign'
DualEndpoint	'DualEndpoint'
DualEndpoint-class	'DualEndpoint'
DualEndpointBeta	'DualEndpointBeta'
DualEndpointBeta-class	'DualEndpointBeta'
DualEndpointEmax	'DualEndpointEmax'
DualEndpointEmax-class	'DualEndpointEmax'
DualEndpointRW	'DualEndpointRW'
DualEndpointRW-class	'DualEndpointRW'
DualResponsesDesign	'DualResponsesDesign.R'
DualResponsesDesign-class	'DualResponsesDesign.R'
DualResponsesSamplesDesign	'DualResponsesSamplesDesign'
DualResponsesSamplesDesign-class	'DualResponsesSamplesDesign'
DualSimulations	'DualSimulations'
DualSimulations-class	'DualSimulations'
DualSimulationsSummary	'DualSimulationsSummary'
DualSimulationsSummary-class	'DualSimulationsSummary'

-- E --

EffFlexi	'EffFlexi'
EffFlexi-class	'EffFlexi'
efficacy	Computing Expected Efficacy for a Given Dose, Model and Samples
efficacy-EffFlexi	Computing Expected Efficacy for a Given Dose, Model and Samples
efficacy-Effloglog	Computing Expected Efficacy for a Given Dose, Model and Samples
efficacy-Effloglog-noSamples	Computing Expected Efficacy for a Given Dose, Model and Samples
efficacy-method	Computing Expected Efficacy for a Given Dose, Model and Samples
efficacyFunction	Getting the Efficacy Function for a Given Model Type
efficacyFunction-method	Getting the Efficacy Function for a Given Model Type
efficacyFunction-ModelEff	Getting the Efficacy Function for a Given Model Type
Effloglog	'Effloglog'
Effloglog-class	'Effloglog'
enable_logging	Verbose Logging
examine	Obtain Hypothetical Trial Course Table for a Design
examine-method	Obtain Hypothetical Trial Course Table for a Design
expect_format	Check that an argument is a valid format specification
expect_probabilities	Check if an argument is a probability vector
expect_probability	Check if an argument is a single probability value
expect_probability_range	Check if an argument is a probability range
expect_range	Check that an argument is a numerical range

-- F --

fit	Fit method for the Samples class
fit-method	Fit method for the Samples class
fitGain	Get the fitted values for the gain values at all dose levels based on a given pseudo DLE model, DLE sample, a pseudo efficacy model, a Efficacy sample and data. This method returns a data frame with dose, middle, lower and upper quantiles of the gain value samples
fitGain-method	Get the fitted values for the gain values at all dose levels based on a given pseudo DLE model, DLE sample, a pseudo efficacy model, a Efficacy sample and data. This method returns a data frame with dose, middle, lower and upper quantiles of the gain value samples
fitPEM	Get the fitted DLT free survival (piecewise exponential model). This function returns a data frame with dose, middle, lower and upper quantiles for the 'PEM' curve. If hazard=TRUE,
fitPEM-method	Get the fitted DLT free survival (piecewise exponential model). This function returns a data frame with dose, middle, lower and upper quantiles for the 'PEM' curve. If hazard=TRUE,
FractionalCRM	'FractionalCRM'
FractionalCRM-class	'FractionalCRM'

-- G --

gain	Compute Gain Values based on Pseudo DLE and a Pseudo Efficacy Models and Using Optional Samples.
gain-method	Compute Gain Values based on Pseudo DLE and a Pseudo Efficacy Models and Using Optional Samples.
gain-ModelTox-Effloglog-noSamples	Compute Gain Values based on Pseudo DLE and a Pseudo Efficacy Models and Using Optional Samples.
gain-ModelTox-ModelEff	Compute Gain Values based on Pseudo DLE and a Pseudo Efficacy Models and Using Optional Samples.
GeneralData	'GeneralData'
GeneralData-class	'GeneralData'
GeneralModel	'GeneralModel'
GeneralModel-class	'GeneralModel'
GeneralSimulations	'GeneralSimulations'
GeneralSimulations-class	'GeneralSimulations'
GeneralSimulationsSummary	'GeneralSimulationsSummary'
GeneralSimulationsSummary-class	'GeneralSimulationsSummary'
get-method	Get specific parameter samples and produce a data.frame
getEff	Extracting Efficacy Responses for Subjects Categorized by the DLT
getEff-DataDual	Extracting Efficacy Responses for Subjects Categorized by the DLT
getEff-method	Extracting Efficacy Responses for Subjects Categorized by the DLT

-- H --

h_all_equivalent	Comparison with Numerical Tolerance and Without Name Comparison
h_blind_plot_data	Helper Function to Blind Plot Data
h_calc_report_label_percentage	Helper function to calculate percentage of true stopping rules for report label output calculates true column means and converts output into percentages before combining the output with the report label; output is passed to 'show()' and output with cat to console
h_check_fun_formals	Checking Formals of a Function
h_convert_ordinal_data	Convert a Ordinal Data to the Equivalent Binary Data for a Specific Grade
h_convert_ordinal_model	Convert an ordinal CRM model to the Equivalent Binary CRM Model for a Specific Grade
h_convert_ordinal_samples	Convert a Samples Object from an ordinal Model to the Equivalent Samples Object from a Binary Model
h_default_if_empty	Getting the default value for an empty object
h_doses_unique_per_cohort	Internal Helper Functions for Validation of 'GeneralData' Objects
h_find_interval	Find Interval Numbers or Indices and Return Custom Number For 0.
h_format_number	Conditional Formatting Using C-style Formats
h_info_theory_dist	Calculating the Information Theoretic Distance
h_in_range	Check which elements are in a given range
h_is_positive_definite	Testing Matrix for Positive Definiteness
h_jags_add_dummy	Appending a Dummy Number for Selected Slots in Data
h_jags_extract_samples	Extracting Samples from 'JAGS' 'mcarray' Object
h_jags_get_data	Getting Data for 'JAGS'
h_jags_get_model_inits	Setting Initial Values for 'JAGS' Model Parameters
h_jags_join_models	Joining 'JAGS' Models
h_jags_write_model	Writing JAGS Model to a File
h_model_dual_endpoint_beta	Update certain components of 'DualEndpoint' model with regard to parameters of the function that models dose-biomarker relationship defined in the 'DualEndpointBeta' class.
h_model_dual_endpoint_rho	Update 'DualEndpoint' class model components with regard to DLT and biomarker correlation.
h_model_dual_endpoint_sigma2betaw	Update certain components of 'DualEndpoint' model with regard to prior variance factor of the random walk.
h_model_dual_endpoint_sigma2w	Update 'DualEndpoint' class model components with regard to biomarker regression variance.
h_next_best_eligible_doses	Get Eligible Doses from the Dose Grid.
h_next_best_mgsamples_plot	Building the Plot for 'nextBest-NextBestMaxGainSamples' Method.
h_next_best_mg_ci	Credibility Intervals for Max Gain and Target Doses at 'nextBest-NextBestMaxGain' Method.
h_next_best_mg_doses_at_grid	Get Closest Grid Doses for a Given Target Doses for 'nextBest-NextBestMaxGain' Method.
h_next_best_mg_plot	Building the Plot for 'nextBest-NextBestMaxGain' Method.
h_next_best_ncrm_loss_plot	Building the Plot for 'nextBest-NextBestNCRMLoss' Method.
h_next_best_tdsamples_plot	Building the Plot for 'nextBest-NextBestTDsamples' Method.
h_next_best_td_plot	Building the Plot for 'nextBest-NextBestTD' Method.
h_null_if_na	Getting 'NULL' for 'NA'
h_obtain_dose_grid_range	Helper Function Containing Common Functionality
h_plot_data_cohort_lines	Preparing Cohort Lines for Data Plot
h_plot_data_dataordinal	Helper Function for the Plot Method of the Data and DataOrdinal Classes
h_plot_data_df	Preparing Data for Plotting
h_plot_data_df-method	Preparing Data for Plotting
h_rapply	Recursively Apply a Function to a List
h_slots	Getting the Slots from a S4 Object
h_summarize_add_stats	Helper function to calculate average across iterations for each additional reporting parameter extracts parameter names as specified by user and averaged the values for each specified parameter to 'show()' and output with cat to console
h_test_named_numeric	Check that an argument is a named vector of type numeric
h_unpack_stopit	Helper function to recursively unpack stopping rules and return lists with logical value and label given
h_validate_combine_results	Combining S4 Class Validation Results
h_validate_common_data_slots	Helper Function performing validation Common to Data and DataOrdinal

-- I --

Increments	'Increments'
Increments-class	'Increments'
IncrementsDoseLevels	'IncrementsDoseLevels'
IncrementsDoseLevels-class	'IncrementsDoseLevels'
IncrementsHSRBeta	'IncrementsHSRBeta'
IncrementsHSRBeta-class	'IncrementsHSRBeta'
IncrementsMaxToxProb	'IncrementsMaxToxProb'
IncrementsMaxToxProb-class	'IncrementsMaxToxProb'
IncrementsMin	'IncrementsMin'
IncrementsMin-class	'IncrementsMin'
IncrementsOrdinal	'IncrementsOrdinal'
IncrementsOrdinal-class	'IncrementsOrdinal'
IncrementsRelative	'IncrementsRelative'
IncrementsRelative-class	'IncrementsRelative'
IncrementsRelativeDLT	'IncrementsRelativeDLT'
IncrementsRelativeDLT-class	'IncrementsRelativeDLT'
IncrementsRelativeDLTCurrent	'IncrementsRelativeDLTCurrent'
IncrementsRelativeDLTCurrent-class	'IncrementsRelativeDLTCurrent'
IncrementsRelativeParts	'IncrementsRelativeParts'
IncrementsRelativeParts-class	'IncrementsRelativeParts'
is_logging_enabled	Verbose Logging

-- K --

knit_print	Render a 'CohortSizeConst' Object
knit_print.CohortSizeConst	Render a 'CohortSizeConst' Object
knit_print.CohortSizeDLT	Render a 'CohortSizeConst' Object
knit_print.CohortSizeMax	Render a 'CohortSizeConst' Object
knit_print.CohortSizeMin	Render a 'CohortSizeConst' Object
knit_print.CohortSizeOrdinal	Render a 'CohortSizeConst' Object
knit_print.CohortSizeParts	Render a 'CohortSizeConst' Object
knit_print.CohortSizeRange	Render a 'CohortSizeConst' Object
knit_print.DADesign	Render a 'CohortSizeConst' Object
knit_print.DataParts	Render a 'CohortSizeConst' Object
knit_print.Design	Render a 'CohortSizeConst' Object
knit_print.DesignGrouped	Render a 'CohortSizeConst' Object
knit_print.DesignOrdinal	Render a 'CohortSizeConst' Object
knit_print.DualDesign	Render a 'CohortSizeConst' Object
knit_print.DualEndpoint	Render a 'CohortSizeConst' Object
knit_print.DualResponsesDesign	Render a 'CohortSizeConst' Object
knit_print.DualResponsesSamplesDesign	Render a 'CohortSizeConst' Object
knit_print.Effloglog	Render a 'CohortSizeConst' Object
knit_print.GeneralData	Render a 'CohortSizeConst' Object
knit_print.GeneralModel	Render a 'CohortSizeConst' Object
knit_print.IncrementsDoseLevels	Render a 'CohortSizeConst' Object
knit_print.IncrementsHSRBeta	Render a 'CohortSizeConst' Object
knit_print.IncrementsMin	Render a 'CohortSizeConst' Object
knit_print.IncrementsOrdinal	Render a 'CohortSizeConst' Object
knit_print.IncrementsRelative	Render a 'CohortSizeConst' Object
knit_print.IncrementsRelativeDLT	Render a 'CohortSizeConst' Object
knit_print.IncrementsRelativeDLTCurrent	Render a 'CohortSizeConst' Object
knit_print.IncrementsRelativeParts	Render a 'CohortSizeConst' Object
knit_print.LogisticIndepBeta	Render a 'CohortSizeConst' Object
knit_print.LogisticKadane	Render a 'CohortSizeConst' Object
knit_print.LogisticKadaneBetaGamma	Render a 'CohortSizeConst' Object
knit_print.LogisticLogNormal	Render a 'CohortSizeConst' Object
knit_print.LogisticLogNormalGrouped	Render a 'CohortSizeConst' Object
knit_print.LogisticLogNormalMixture	Render a 'CohortSizeConst' Object
knit_print.LogisticLogNormalOrdinal	Render a 'CohortSizeConst' Object
knit_print.LogisticLogNormalSub	Render a 'CohortSizeConst' Object
knit_print.LogisticNormalFixedMixture	Render a 'CohortSizeConst' Object
knit_print.LogisticNormalMixture	Render a 'CohortSizeConst' Object
knit_print.ModelParamsNormal	Render a 'CohortSizeConst' Object
knit_print.NextBestDualEndpoint	Render a 'CohortSizeConst' Object
knit_print.NextBestInfTheory	Render a 'CohortSizeConst' Object
knit_print.NextBestMaxGain	Render a 'CohortSizeConst' Object
knit_print.NextBestMaxGainSamples	Render a 'CohortSizeConst' Object
knit_print.NextBestMinDist	Render a 'CohortSizeConst' Object
knit_print.NextBestMTD	Render a 'CohortSizeConst' Object
knit_print.NextBestNCRM	Render a 'CohortSizeConst' Object
knit_print.NextBestNCRMLoss	Render a 'CohortSizeConst' Object
knit_print.NextBestOrdinal	Render a 'CohortSizeConst' Object
knit_print.NextBestProbMTDLTE	Render a 'CohortSizeConst' Object
knit_print.NextBestProbMTDMinDist	Render a 'CohortSizeConst' Object
knit_print.NextBestTD	Render a 'CohortSizeConst' Object
knit_print.NextBestTDsamples	Render a 'CohortSizeConst' Object
knit_print.NextBestThreePlusThree	Render a 'CohortSizeConst' Object
knit_print.OneParExpPrior	Render a 'CohortSizeConst' Object
knit_print.OneParLogNormalPrior	Render a 'CohortSizeConst' Object
knit_print.RuleDesign	Render a 'CohortSizeConst' Object
knit_print.RuleDesignOrdinal	Render a 'CohortSizeConst' Object
knit_print.SafetyWindow	Render a 'CohortSizeConst' Object
knit_print.SafetyWindowConst	Render a 'CohortSizeConst' Object
knit_print.SafetyWindowSize	Render a 'CohortSizeConst' Object
knit_print.StartingDose	Render a 'CohortSizeConst' Object
knit_print.StoppingAll	Render a 'CohortSizeConst' Object
knit_print.StoppingAny	Render a 'CohortSizeConst' Object
knit_print.StoppingCohortsNearDose	Render a 'CohortSizeConst' Object
knit_print.StoppingHighestDose	Render a 'CohortSizeConst' Object
knit_print.StoppingList	Render a 'CohortSizeConst' Object
knit_print.StoppingLowestDoseHSRBeta	Render a 'CohortSizeConst' Object
knit_print.StoppingMaxGainCIRatio	Render a 'CohortSizeConst' Object
knit_print.StoppingMinCohorts	Render a 'CohortSizeConst' Object
knit_print.StoppingMinPatients	Render a 'CohortSizeConst' Object
knit_print.StoppingMissingDose	Render a 'CohortSizeConst' Object
knit_print.StoppingMTDCV	Render a 'CohortSizeConst' Object
knit_print.StoppingMTDdistribution	Render a 'CohortSizeConst' Object
knit_print.StoppingOrdinal	Render a 'CohortSizeConst' Object
knit_print.StoppingPatientsNearDose	Render a 'CohortSizeConst' Object
knit_print.StoppingSpecificDose	Render a 'CohortSizeConst' Object
knit_print.StoppingTargetBiomarker	Render a 'CohortSizeConst' Object
knit_print.StoppingTargetProb	Render a 'CohortSizeConst' Object
knit_print.StoppingTDCIRatio	Render a 'CohortSizeConst' Object
knit_print.TDDesign	Render a 'CohortSizeConst' Object
knit_print.TDsamplesDesign	Render a 'CohortSizeConst' Object

-- L --

LogisticIndepBeta	'LogisticIndepBeta'
LogisticIndepBeta-class	'LogisticIndepBeta'
LogisticKadane	'LogisticKadane'
LogisticKadane-class	'LogisticKadane'
LogisticKadaneBetaGamma	'LogisticKadaneBetaGamma'
LogisticKadaneBetaGamma-class	'LogisticKadaneBetaGamma'
LogisticLogNormal	'LogisticLogNormal'
LogisticLogNormal-class	'LogisticLogNormal'
LogisticLogNormalGrouped	'LogisticLogNormalGrouped'
LogisticLogNormalGrouped-class	'LogisticLogNormalGrouped'
LogisticLogNormalMixture	'LogisticLogNormalMixture'
LogisticLogNormalMixture-class	'LogisticLogNormalMixture'
LogisticLogNormalOrdinal	'LogisticLogNormalOrdinal'
LogisticLogNormalOrdinal-class	'LogisticLogNormalOrdinal'
LogisticLogNormalSub	'LogisticLogNormalSub'
LogisticLogNormalSub-class	'LogisticLogNormalSub'
LogisticNormal	'LogisticNormal'
LogisticNormal-class	'LogisticNormal'
LogisticNormalFixedMixture	'LogisticNormalFixedMixture'
LogisticNormalFixedMixture-class	'LogisticNormalFixedMixture'
LogisticNormalMixture	'LogisticNormalMixture'
LogisticNormalMixture-class	'LogisticNormalMixture'
logit	Shorthand for Logit Function
log_trace	Verbose Logging

-- M --

match_within_tolerance	Helper Function for Value Matching with Tolerance
maxDose	Determine the Maximum Possible Next Dose
maxDose-IncrementsDoseLevels	Determine the Maximum Possible Next Dose
maxDose-IncrementsHSRBeta	Determine the Maximum Possible Next Dose
maxDose-IncrementsMaxToxProb	Determine the Maximum Possible Next Dose
maxDose-IncrementsMin	Determine the Maximum Possible Next Dose
maxDose-IncrementsOrdinal	Determine the Maximum Possible Next Dose
maxDose-IncrementsRelative	Determine the Maximum Possible Next Dose
maxDose-IncrementsRelativeDLT	Determine the Maximum Possible Next Dose
maxDose-IncrementsRelativeDLTCurrent	Determine the Maximum Possible Next Dose
maxDose-IncrementsRelativeParts	Determine the Maximum Possible Next Dose
maxDose-method	Determine the Maximum Possible Next Dose
maxSize	"MAX" Combination of Cohort Size Rules
maxSize-CohortSize	"MAX" Combination of Cohort Size Rules
maxSize-method	"MAX" Combination of Cohort Size Rules
mcmc	Obtaining Posterior Samples for all Model Parameters
mcmc-Data-LogisticIndepBeta	Obtaining Posterior Samples for all Model Parameters
mcmc-DataDual-EffFlexi	Obtaining Posterior Samples for all Model Parameters
mcmc-DataDual-Effloglog	Obtaining Posterior Samples for all Model Parameters
mcmc-DataMixture	Obtaining Posterior Samples for all Model Parameters
mcmc-DataOrdinal-LogisticLogNormalOrdinal	Obtaining Posterior Samples for all Model Parameters
mcmc-GeneralData	Obtaining Posterior Samples for all Model Parameters
mcmc-GeneralData-DualEndpointBeta	Obtaining Posterior Samples for all Model Parameters
mcmc-GeneralData-DualEndpointEmax	Obtaining Posterior Samples for all Model Parameters
mcmc-GeneralData-DualEndpointRW	Obtaining Posterior Samples for all Model Parameters
mcmc-GeneralData-OneParExpPrior	Obtaining Posterior Samples for all Model Parameters
mcmc-GeneralData-OneParLogNormalPrior	Obtaining Posterior Samples for all Model Parameters
mcmc-method	Obtaining Posterior Samples for all Model Parameters
McmcOptions	'McmcOptions'
McmcOptions-class	'McmcOptions'
MinimalInformative	Construct a Minimally Informative Prior
minSize	"MIN" Combination of Cohort Size Rules
minSize-CohortSize	"MIN" Combination of Cohort Size Rules
minSize-method	"MIN" Combination of Cohort Size Rules
ModelEff	'ModelEff'
ModelEff-class	'ModelEff'
ModelLogNormal	'ModelLogNormal'
ModelLogNormal-class	'ModelLogNormal'
ModelParamsNormal	'ModelParamsNormal'
ModelParamsNormal-class	'ModelParamsNormal'
ModelPseudo	'ModelPseudo'
ModelPseudo-class	'ModelPseudo'
ModelTox	'ModelTox'
ModelTox-class	'ModelTox'

-- N --

names-method	The Names of the Sampled Parameters
names-Samples	The Names of the Sampled Parameters
NextBest	'NextBest'
nextBest	Finding the Next Best Dose
NextBest-class	'NextBest'
nextBest-method	Finding the Next Best Dose
nextBest-NextBestDualEndpoint	Finding the Next Best Dose
nextBest-NextBestEWOC	Finding the Next Best Dose
nextBest-NextBestInfTheory	Finding the Next Best Dose
nextBest-NextBestMaxGain	Finding the Next Best Dose
nextBest-NextBestMaxGainSamples	Finding the Next Best Dose
nextBest-NextBestMinDist	Finding the Next Best Dose
nextBest-NextBestMTD	Finding the Next Best Dose
nextBest-NextBestNCRM	Finding the Next Best Dose
nextBest-NextBestNCRM-DataParts	Finding the Next Best Dose
nextBest-NextBestNCRMLoss	Finding the Next Best Dose
nextBest-NextBestOrdinal	Finding the Next Best Dose
nextBest-NextBestProbMTDLTE	Finding the Next Best Dose
nextBest-NextBestProbMTDMinDist	Finding the Next Best Dose
nextBest-NextBestTD	Finding the Next Best Dose
nextBest-NextBestTDsamples	Finding the Next Best Dose
nextBest-NextBestThreePlusThree	Finding the Next Best Dose
NextBestDualEndpoint	'NextBestDualEndpoint'
NextBestDualEndpoint-class	'NextBestDualEndpoint'
NextBestEWOC	'NextBestEWOC'
NextBestEWOC-class	'NextBestEWOC'
NextBestInfTheory	'NextBestInfTheory'
NextBestInfTheory-class	'NextBestInfTheory'
NextBestMaxGain	'NextBestMaxGain'
NextBestMaxGain-class	'NextBestMaxGain'
NextBestMaxGainSamples	'NextBestMaxGainSamples'
NextBestMaxGainSamples-class	'NextBestMaxGainSamples'
NextBestMinDist	'NextBestMinDist'
NextBestMinDist-class	'NextBestMinDist'
NextBestMTD	'NextBestMTD'
NextBestMTD-class	'NextBestMTD'
NextBestNCRM	'NextBestNCRM'
NextBestNCRM-class	'NextBestNCRM'
NextBestNCRMLoss	'NextBestNCRMLoss'
NextBestNCRMLoss-class	'NextBestNCRMLoss'
NextBestOrdinal	'NextBestOrdinal'
NextBestOrdinal-class	'NextBestOrdinal'
NextBestProbMTDLTE	'NextBestProbMTDLTE'
NextBestProbMTDLTE-class	'NextBestProbMTDLTE'
NextBestProbMTDMinDist	'NextBestProbMTDMinDist'
NextBestProbMTDMinDist-class	'NextBestProbMTDMinDist'
NextBestTD	'NextBestTD'
NextBestTD-class	'NextBestTD'
NextBestTDsamples	'NextBestTDsamples'
NextBestTDsamples-class	'NextBestTDsamples'
NextBestThreePlusThree	'NextBestThreePlusThree'
NextBestThreePlusThree-class	'NextBestThreePlusThree'
ngrid	Number of Doses in Grid
ngrid-Data	Number of Doses in Grid
ngrid-method	Number of Doses in Grid

-- O --

OneParExpPrior	'OneParExpPrior'
OneParExpPrior-class	'OneParExpPrior'
OneParLogNormalPrior	'OneParLogNormalPrior'
OneParLogNormalPrior-class	'OneParLogNormalPrior'
or-Stopping-Stopping	Combine Two Stopping Rules with OR
or-Stopping-StoppingAny	Combine an Atomic Stopping Rule and a Stopping List with OR
or-StoppingAny-Stopping	Combine a Stopping List and an Atomic Stopping Rule with OR

-- P --

plot-Data	Helper Function for the Plot Method of the Data and DataOrdinal Classes
plot-DataDA	Plot Method for the 'DataDA' Class
plot-DataDual	Plot Method for the 'DataDual' Class
plot-DualSimulations-missing	Plot 'DualSimulations'
plot-DualSimulationsSummary-missing	Plot Dual-Endpoint Design Simulation Summary
plot-GeneralSimulations-missing	Plot 'GeneralSimulations'
plot-GeneralSimulationsSummary-missing	Plot 'GeneralSimulationsSummary'
plot-method	Plot of the fitted dose-tox based with a given pseudo DLE model and data without samples
plot-method	Helper Function for the Plot Method of the Data and DataOrdinal Classes
plot-method	Plot Method for the 'DataDA' Class
plot-method	Plot of the fitted dose-efficacy based with a given pseudo efficacy model and data without samples
plot-method	Plot Method for the 'DataDual' Class
plot-method	Plot 'DualSimulations'
plot-method	Plot Dual-Endpoint Design Simulation Summary
plot-method	Plot 'GeneralSimulations'
plot-method	Plot 'GeneralSimulationsSummary'
plot-method	Plot 'PseudoDualFlexiSimulations'
plot-method	Plot 'PseudoDualSimulations'
plot-method	Plot 'PseudoDualSimulationsSummary'
plot-method	Plot 'PseudoSimulationsSummary'
plot-method	Plotting dose-toxicity model fits
plot-method	Plotting dose-toxicity and dose-biomarker model fits
plot-method	Plotting dose-toxicity model fits
plot-method	Plot the fitted dose-efficacy curve using a model from 'ModelEff' class with samples
plot-method	Plot the fitted dose-DLE curve using a 'ModelTox' class model with samples
plot-method	Plot Model-Based Design Simulation Summary
plot-PseudoDualFlexiSimulations-missing	Plot 'PseudoDualFlexiSimulations'
plot-PseudoDualSimulations-missing	Plot 'PseudoDualSimulations'
plot-PseudoDualSimulationsSummary-missing	Plot 'PseudoDualSimulationsSummary'
plot-PseudoSimulationsSummary-missing	Plot 'PseudoSimulationsSummary'
plot-SimulationsSummary-missing	Plot Model-Based Design Simulation Summary
plot.gtable	Plot 'gtable' Objects
plotDualResponses	Plot of the DLE and efficacy curve side by side given a DLE pseudo model, a DLE sample, an efficacy pseudo model and a given efficacy sample
plotDualResponses-method	Plot of the DLE and efficacy curve side by side given a DLE pseudo model, a DLE sample, an efficacy pseudo model and a given efficacy sample
plotGain	Plot the gain curve in addition with the dose-DLE and dose-efficacy curve using a given DLE pseudo model, a DLE sample, a given efficacy pseudo model and an efficacy sample
plotGain-method	Plot the gain curve in addition with the dose-DLE and dose-efficacy curve using a given DLE pseudo model, a DLE sample, a given efficacy pseudo model and an efficacy sample
positive_number	'positive_number'
print.gtable	Plot 'gtable' Objects
prob	Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-DualEndpoint	Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-LogisticIndepBeta	Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-LogisticIndepBeta-noSamples	Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-LogisticKadane	Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-LogisticKadaneBetaGamma	Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-LogisticLogNormal	Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-LogisticLogNormalGrouped	Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-LogisticLogNormalMixture	Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-LogisticLogNormalOrdinal	Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-LogisticLogNormalSub	Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-LogisticNormal	Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-LogisticNormalFixedMixture	Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-LogisticNormalMixture	Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-method	Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-OneParExpPrior	Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-OneParLogNormalPrior	Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-ProbitLogNormal	Computing Toxicity Probabilities for a Given Dose, Model and Samples
prob-ProbitLogNormalRel	Computing Toxicity Probabilities for a Given Dose, Model and Samples
probFunction	Getting the Prob Function for a Given Model Type
probFunction-GeneralModel	Getting the Prob Function for a Given Model Type
probFunction-LogisticLogNormalOrdinal	Getting the Prob Function for a Given Model Type
probFunction-method	Getting the Prob Function for a Given Model Type
probFunction-ModelTox	Getting the Prob Function for a Given Model Type
probit	Shorthand for Probit Function
ProbitLogNormal	'ProbitLogNormal'
ProbitLogNormal-class	'ProbitLogNormal'
ProbitLogNormalLogDose	'ProbitLogNormal'
ProbitLogNormalRel	'ProbitLogNormalRel'
ProbitLogNormalRel-class	'ProbitLogNormalRel'
PseudoDualFlexiSimulations	'PseudoDualFlexiSimulations'
PseudoDualFlexiSimulations-class	'PseudoDualFlexiSimulations'
PseudoDualSimulations	'PseudoDualSimulations'
PseudoDualSimulations-class	'PseudoDualSimulations'
PseudoDualSimulationsSummary	'PseudoDualSimulationsSummary'
PseudoDualSimulationsSummary-class	'PseudoDualSimulationsSummary'
PseudoSimulations	'PseudoSimulations'
PseudoSimulations-class	'PseudoSimulations'
PseudoSimulationsSummary	'PseudoSimulationsSummary'
PseudoSimulationsSummary-class	'PseudoSimulationsSummary'

-- Q --

Quantiles2LogisticNormal

Convert Prior Quantiles to Logistic (Log) Normal Model

-- R --

RuleDesign	'RuleDesign'
RuleDesign-class	'RuleDesign'
RuleDesignOrdinal	'RuleDesignOrdinal'
RuleDesignOrdinal-class	'RuleDesignOrdinal'

-- S --

SafetyWindow	'SafetyWindow'
SafetyWindow-class	'SafetyWindow'
SafetyWindowConst	'SafetyWindowConst'
SafetyWindowConst-class	'SafetyWindowConst'
SafetyWindowSize	'SafetyWindowSize'
SafetyWindowSize-class	'SafetyWindowSize'
Samples	'Samples'
Samples-class	'Samples'
saveSample	Determining if this Sample Should be Saved
saveSample-McmcOptions	Determining if this Sample Should be Saved
saveSample-method	Determining if this Sample Should be Saved
set_seed	Helper Function to Set and Save the RNG Seed
show-DualSimulationsSummary	Show the Summary of Dual-Endpoint Simulations
show-GeneralSimulationsSummary	Show the Summary of the Simulations
show-method	Show the Summary of Dual-Endpoint Simulations
show-method	Show the Summary of the Simulations
show-method	Show the Summary of 'PseudoDualSimulations'
show-method	Show the Summary of 'PseudoSimulations'
show-method	Show the Summary of Model-Based Design Simulations
show-PseudoDualSimulationsSummary	Show the Summary of 'PseudoDualSimulations'
show-PseudoSimulationsSummary	Show the Summary of 'PseudoSimulations'
show-SimulationsSummary	Show the Summary of Model-Based Design Simulations
simulate-DesignGrouped	Simulate Method for the 'DesignGrouped' Class
simulate-method	Simulate outcomes from a time-to-DLT augmented CRM design
simulate-method	Simulate outcomes from a CRM design
simulate-method	Simulate Method for the 'DesignGrouped' Class
simulate-method	Simulate outcomes from a dual-endpoint design
simulate-method	Simulate dose escalation procedure using both DLE and efficacy responses without samples
simulate-method	Simulate dose escalation procedure using DLE and efficacy responses with samples
simulate-method	Simulate outcomes from a rule-based design
simulate-method	Simulate dose escalation procedure using DLE responses only without samples
simulate-method	Simulate dose escalation procedure using DLE responses only with DLE samples
Simulations	'Simulations'
Simulations-class	'Simulations'
SimulationsSummary	'SimulationsSummary'
SimulationsSummary-class	'SimulationsSummary'
size	Size of an Object
size-CohortSizeConst	Size of an Object
size-CohortSizeDLT	Size of an Object
size-CohortSizeMax	Size of an Object
size-CohortSizeMin	Size of an Object
size-CohortSizeOrdinal	Size of an Object
size-CohortSizeParts	Size of an Object
size-CohortSizeRange	Size of an Object
size-McmcOptions	Size of an Object
size-method	Size of an Object
size-Samples	Size of an Object
Stopping	'Stopping'
Stopping-class	'Stopping'
StoppingAll	'StoppingAll'
StoppingAll-class	'StoppingAll'
StoppingAny	'StoppingAny'
StoppingAny-class	'StoppingAny'
StoppingCohortsNearDose	'StoppingCohortsNearDose'
StoppingCohortsNearDose-class	'StoppingCohortsNearDose'
StoppingExternal	'StoppingExternal'
StoppingExternal-class	'StoppingExternal'
StoppingHighestDose	'StoppingHighestDose'
StoppingHighestDose-class	'StoppingHighestDose'
StoppingList	'StoppingList'
StoppingList-class	'StoppingList'
StoppingLowestDoseHSRBeta	'StoppingLowestDoseHSRBeta'
StoppingLowestDoseHSRBeta-class	'StoppingLowestDoseHSRBeta'
StoppingMaxGainCIRatio	'StoppingMaxGainCIRatio'
StoppingMaxGainCIRatio-class	'StoppingMaxGainCIRatio'
StoppingMinCohorts	'StoppingMinCohorts'
StoppingMinCohorts-class	'StoppingMinCohorts'
StoppingMinPatients	'StoppingMinPatients'
StoppingMinPatients-class	'StoppingMinPatients'
StoppingMissingDose	'StoppingMissingDose'
StoppingMissingDose-class	'StoppingMissingDose'
StoppingMTDCV	'StoppingMTDCV'
StoppingMTDCV-class	'StoppingMTDCV'
StoppingMTDdistribution	'StoppingMTDdistribution'
StoppingMTDdistribution-class	'StoppingMTDdistribution'
StoppingOrdinal	'StoppingOrdinal'
StoppingOrdinal-class	'StoppingOrdinal'
StoppingPatientsNearDose	'StoppingPatientsNearDose'
StoppingPatientsNearDose-class	'StoppingPatientsNearDose'
StoppingSpecificDose	'StoppingSpecificDose'
StoppingSpecificDose-class	'StoppingSpecificDose'
StoppingTargetBiomarker	'StoppingTargetBiomarker'
StoppingTargetBiomarker-class	'StoppingTargetBiomarker'
StoppingTargetProb	'StoppingTargetProb'
StoppingTargetProb-class	'StoppingTargetProb'
StoppingTDCIRatio	'StoppingTDCIRatio'
StoppingTDCIRatio-class	'StoppingTDCIRatio'
stopTrial	Stop the trial?
stopTrial-method	Stop the trial?
stopTrial-StoppingAll	Stop the trial?
stopTrial-StoppingAny	Stop the trial?
stopTrial-StoppingCohortsNearDose	Stop the trial?
stopTrial-StoppingExternal	Stop the trial?
stopTrial-StoppingHighestDose	Stop the trial?
stopTrial-StoppingList	Stop the trial?
stopTrial-StoppingLowestDoseHSRBeta	Stop the trial?
stopTrial-StoppingMaxGainCIRatio	Stop the trial?
stopTrial-StoppingMinCohorts	Stop the trial?
stopTrial-StoppingMinPatients	Stop the trial?
stopTrial-StoppingMissingDose	Stop the trial?
stopTrial-StoppingMTDCV	Stop the trial?
stopTrial-StoppingMTDdistribution	Stop the trial?
stopTrial-StoppingOrdinal	Stop the trial?
stopTrial-StoppingPatientsNearDose	Stop the trial?
stopTrial-StoppingSpecificDose	Stop the trial?
stopTrial-StoppingTargetBiomarker	Stop the trial?
stopTrial-StoppingTargetProb	Stop the trial?
stopTrial-StoppingTDCIRatio	Stop the trial?
summary-DualSimulations	Summarize Dual-Endpoint Design Simulations
summary-GeneralSimulations	Summarize the 'GeneralSimulations', Relative to a Given Truth
summary-method	Summarize Dual-Endpoint Design Simulations
summary-method	Summarize the 'GeneralSimulations', Relative to a Given Truth
summary-method	Summarize 'PseudoDualFlexiSimulations'
summary-method	Summarize 'PseudoDualSimulations'
summary-method	Summarize 'PseudoSimulations'
summary-method	Summarize Model-Based Design Simulations
summary-PseudoDualFlexiSimulations	Summarize 'PseudoDualFlexiSimulations'
summary-PseudoDualSimulations	Summarize 'PseudoDualSimulations'
summary-PseudoSimulations	Summarize 'PseudoSimulations'
summary-Simulations	Summarize Model-Based Design Simulations

-- T --

TDDesign	'TDDesign'
TDDesign-class	'TDDesign'
TDsamplesDesign	'TDsamplesDesign'
TDsamplesDesign-class	'TDsamplesDesign'
test_format	Check that an argument is a valid format specification
test_length	Check if vectors are of compatible lengths
test_probabilities	Check if an argument is a probability vector
test_probability	Check if an argument is a single probability value
test_probability_range	Check if an argument is a probability range
test_range	Check that an argument is a numerical range
ThreePlusThreeDesign	'RuleDesign'
tidy	Tidying 'CrmPackClass' objects
tidy-CohortSizeDLT	Tidying 'CrmPackClass' objects
tidy-CohortSizeMax	Tidying 'CrmPackClass' objects
tidy-CohortSizeMin	Tidying 'CrmPackClass' objects
tidy-CohortSizeParts	Tidying 'CrmPackClass' objects
tidy-CohortSizeRange	Tidying 'CrmPackClass' objects
tidy-CrmPackClass	Tidying 'CrmPackClass' objects
tidy-DataDA	Tidying 'CrmPackClass' objects
tidy-DataDual	Tidying 'CrmPackClass' objects
tidy-DataGrouped	Tidying 'CrmPackClass' objects
tidy-DataMixture	Tidying 'CrmPackClass' objects
tidy-DataOrdinal	Tidying 'CrmPackClass' objects
tidy-DataParts	Tidying 'CrmPackClass' objects
tidy-DualDesign	Tidying 'CrmPackClass' objects
tidy-Effloglog	Tidying 'CrmPackClass' objects
tidy-GeneralData	Tidying 'CrmPackClass' objects
tidy-IncrementsMaxToxProb	Tidying 'CrmPackClass' objects
tidy-IncrementsMin	Tidying 'CrmPackClass' objects
tidy-IncrementsRelative	Tidying 'CrmPackClass' objects
tidy-IncrementsRelativeDLT	Tidying 'CrmPackClass' objects
tidy-IncrementsRelativeParts	Tidying 'CrmPackClass' objects
tidy-LogisticIndepBeta	Tidying 'CrmPackClass' objects
tidy-method	Tidying 'CrmPackClass' objects
tidy-NextBestNCRM	Tidying 'CrmPackClass' objects
tidy-NextBestNCRMLoss	Tidying 'CrmPackClass' objects
tidy-Samples	Tidying 'CrmPackClass' objects
tidy-Simulations	Tidying 'CrmPackClass' objects
TITELogisticLogNormal	'TITELogisticLogNormal'
TITELogisticLogNormal-class	'TITELogisticLogNormal'

-- U --

update-Data	Updating 'Data' Objects
update-DataDA	Updating 'DataDA' Objects
update-DataDual	Updating 'DataDual' Objects
update-DataOrdinal	Updating 'DataOrdinal' Objects
update-DataParts	Updating 'DataParts' Objects
update-method	Updating 'Data' Objects
update-method	Updating 'DataDA' Objects
update-method	Updating 'DataDual' Objects
update-method	Updating 'DataOrdinal' Objects
update-method	Updating 'DataParts' Objects
update-method	Update method for the 'ModelPseudo' model class. This is a method to update the model class slots (estimates, parameters, variables and etc.), when the new data (e.g. new observations of responses) are available. This method is mostly used to obtain new modal estimates for pseudo model parameters.
update-ModelPseudo	Update method for the 'ModelPseudo' model class. This is a method to update the model class slots (estimates, parameters, variables and etc.), when the new data (e.g. new observations of responses) are available. This method is mostly used to obtain new modal estimates for pseudo model parameters.

-- V --

Validate	'Validate'
v_cohort_size	Internal Helper Functions for Validation of 'CohortSize' Objects
v_cohort_size_const	Internal Helper Functions for Validation of 'CohortSize' Objects
v_cohort_size_dlt	Internal Helper Functions for Validation of 'CohortSize' Objects
v_cohort_size_max	Internal Helper Functions for Validation of 'CohortSize' Objects
v_cohort_size_ordinal	Internal Helper Functions for Validation of 'Increments' Objects
v_cohort_size_parts	Internal Helper Functions for Validation of 'CohortSize' Objects
v_cohort_size_range	Internal Helper Functions for Validation of 'CohortSize' Objects
v_data	Internal Helper Functions for Validation of 'GeneralData' Objects
v_data_da	Internal Helper Functions for Validation of 'GeneralData' Objects
v_data_dual	Internal Helper Functions for Validation of 'GeneralData' Objects
v_data_grouped	Internal Helper Functions for Validation of 'GeneralData' Objects
v_data_mixture	Internal Helper Functions for Validation of 'GeneralData' Objects
v_data_objects	Internal Helper Functions for Validation of 'GeneralData' Objects
v_data_ordinal	Internal Helper Functions for Validation of 'GeneralData' Objects
v_data_parts	Internal Helper Functions for Validation of 'GeneralData' Objects
v_da_simulations	Internal Helper Functions for Validation of 'GeneralSimulations' Objects
v_design	Internal Helper Functions for Validation of 'RuleDesign' Objects
v_design_grouped	Internal Helper Functions for Validation of 'RuleDesign' Objects
v_dual_simulations	Internal Helper Functions for Validation of 'GeneralSimulations' Objects
v_general_data	Internal Helper Functions for Validation of 'GeneralData' Objects
v_general_model	Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_general_simulations	Internal Helper Functions for Validation of 'GeneralSimulations' Objects
v_increments	Internal Helper Functions for Validation of 'Increments' Objects
v_increments_dose_levels	Internal Helper Functions for Validation of 'Increments' Objects
v_increments_hsr_beta	Internal Helper Functions for Validation of 'Increments' Objects
v_increments_maxtoxprob	Internal Helper Functions for Validation of 'Increments' Objects
v_increments_min	Internal Helper Functions for Validation of 'Increments' Objects
v_increments_ordinal	Internal Helper Functions for Validation of 'Increments' Objects
v_increments_relative	Internal Helper Functions for Validation of 'Increments' Objects
v_increments_relative_dlt	Internal Helper Functions for Validation of 'Increments' Objects
v_increments_relative_parts	Internal Helper Functions for Validation of 'Increments' Objects
v_logisticlognormalordinal	Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_mcmcoptions_objects	Internal Helper Functions for Validation of 'McmcOptions' Objects
v_mcmc_options	Internal Helper Functions for Validation of 'McmcOptions' Objects
v_model_da_logistic_log_normal	Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_dual_endpoint	Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_dual_endpoint_beta	Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_dual_endpoint_emax	Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_dual_endpoint_rw	Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_eff_flexi	Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_eff_log_log	Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_logistic_indep_beta	Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_logistic_kadane	Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_logistic_kadane_beta_gamma	Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_logistic_log_normal_mix	Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_logistic_normal_fixed_mix	Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_logistic_normal_mix	Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_objects	Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_one_par_exp_normal_prior	Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_one_par_exp_prior	Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_model_params	Internal Helper Functions for Validation of Model Parameters Objects
v_model_params_normal	Internal Helper Functions for Validation of Model Parameters Objects
v_model_tite_logistic_log_normal	Internal Helper Functions for Validation of 'GeneralModel' and 'ModelPseudo' Objects
v_next_best	Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_dual_endpoint	Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_ewoc	Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_inf_theory	Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_max_gain_samples	Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_min_dist	Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_mtd	Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_ncrm	Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_ncrm_loss	Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_ordinal	Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_prob_mtd_lte	Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_prob_mtd_min_dist	Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_td	Internal Helper Functions for Validation of 'NextBest' Objects
v_next_best_td_samples	Internal Helper Functions for Validation of 'NextBest' Objects
v_pseudo_dual_flex_simulations	Internal Helper Functions for Validation of 'PseudoSimulations' Objects
v_pseudo_dual_simulations	Internal Helper Functions for Validation of 'PseudoSimulations' Objects
v_pseudo_simulations	Internal Helper Functions for Validation of 'PseudoSimulations' Objects
v_rule_design	Internal Helper Functions for Validation of 'RuleDesign' Objects
v_rule_design_ordinal	Internal Helper Functions for Validation of 'RuleDesign' Objects
v_safety_window	Internal Helper Functions for Validation of 'SafetyWindow' Objects
v_safety_window_const	Internal Helper Functions for Validation of 'SafetyWindow' Objects
v_safety_window_size	Internal Helper Functions for Validation of 'SafetyWindow' Objects
v_samples	Internal Helper Functions for Validation of 'Samples' Objects
v_samples_objects	Internal Helper Functions for Validation of 'Samples' Objects
v_simulations	Internal Helper Functions for Validation of 'GeneralSimulations' Objects
v_stopping	Internal Helper Functions for Validation of 'Stopping' Objects
v_stopping_all	Internal Helper Functions for Validation of 'Stopping' Objects
v_stopping_cohorts_near_dose	Internal Helper Functions for Validation of 'Stopping' Objects
v_stopping_list	Internal Helper Functions for Validation of 'Stopping' Objects
v_stopping_min_cohorts	Internal Helper Functions for Validation of 'Stopping' Objects
v_stopping_min_patients	Internal Helper Functions for Validation of 'Stopping' Objects
v_stopping_mtd_cv	Internal Helper Functions for Validation of 'Stopping' Objects
v_stopping_mtd_distribution	Internal Helper Functions for Validation of 'Stopping' Objects
v_stopping_patients_near_dose	Internal Helper Functions for Validation of 'Stopping' Objects
v_stopping_target_biomarker	Internal Helper Functions for Validation of 'Stopping' Objects
v_stopping_target_prob	Internal Helper Functions for Validation of 'Stopping' Objects
v_stopping_tdci_ratio	Internal Helper Functions for Validation of 'Stopping' Objects

-- W --

windowLength	Determine the Safety Window Length of the Next Cohort
windowLength-method	Determine the Safety Window Length of the Next Cohort
windowLength-SafetyWindowConst	Determine the Safety Window Length of the Next Cohort
windowLength-SafetyWindowSize	Determine the Safety Window Length of the Next Cohort

-- misc --

&-method	Combine Two Stopping Rules with AND
&-method	Combine an Atomic Stopping Rule and a Stopping List with AND
&-method	Combine a Stopping List and an Atomic Stopping Rule with AND
.CohortSizeConst	'CohortSizeConst'
.CohortSizeDLT	'CohortSizeDLT'
.CohortSizeMax	'CohortSizeMax'
.CohortSizeMin	'CohortSizeMin'
.CohortSizeOrdinal	'CohortSizeOrdinal'
.CohortSizeParts	'CohortSizeParts'
.CohortSizeRange	'CohortSizeRange'
.CrmPackClass	'CrmPackClass'
.DADesign	'DADesign'
.DALogisticLogNormal	'DALogisticLogNormal'
.DASimulations	'DASimulations'
.Data	'Data'
.DataDA	'DataDA'
.DataDual	'DataDual'
.DataGrouped	'DataGrouped'
.DataMixture	'DataMixture'
.DataOrdinal	'DataOrdinal'
.DataParts	'DataParts'
.DefaultCohortSize	'CohortSize'
.DefaultCohortSizeConst	'CohortSizeConst'
.DefaultCohortSizeDLT	'CohortSizeDLT'
.DefaultCohortSizeMax	'CohortSizeMax'
.DefaultCohortSizeMin	'CohortSizeMin'
.DefaultCohortSizeOrdinal	'CohortSizeOrdinal'
.DefaultCohortSizeParts	'CohortSizeParts'
.DefaultCohortSizeRange	'CohortSizeRange'
.DefaultDADesign	'DADesign'
.DefaultDALogisticLogNormal	'DALogisticLogNormal'
.DefaultDASimulations	'DASimulations'
.DefaultData	'Data'
.DefaultDataDA	'DataDA'
.DefaultDataDual	'DataDual'
.DefaultDataGeneral	'GeneralData'
.DefaultDataGrouped	'DataGrouped'
.DefaultDataMixture	'DataMixture'
.DefaultDataOrdinal	'DataOrdinal'
.DefaultDataParts	'DataParts'
.DefaultDesign	'Design'
.DefaultDesignGrouped	'DesignGrouped'
.DefaultDesignOrdinal	'DesignOrdinal'
.DefaultDualDesign	'DualDesign'
.DefaultDualEndpoint	'DualEndpoint'
.DefaultDualEndpointBeta	'DualEndpointBeta'
.DefaultDualEndpointEmax	'DualEndpointEmax'
.DefaultDualEndpointRW	'DualEndpointRW'
.DefaultDualResponsesDesign	'DualResponsesDesign.R'
.DefaultDualResponsesSamplesDesign	'DualResponsesSamplesDesign'
.DefaultDualSimulations	'DualSimulations'
.DefaultDualSimulationsSummary	'DualSimulationsSummary'
.DefaultEffFlexi	'EffFlexi'
.DefaultEffloglog	'Effloglog'
.DefaultFractionalCRM	'FractionalCRM'
.DefaultGeneralModel	'GeneralModel'
.DefaultGeneralSimulations	'GeneralSimulations'
.DefaultGeneralSimulationsSummary	'GeneralSimulationsSummary'
.DefaultIncrements	'Increments'
.DefaultIncrementsDoseLevels	'IncrementsDoseLevels'
.DefaultIncrementsHSRBeta	'IncrementsHSRBeta'
.DefaultIncrementsMaxToxProb	'IncrementsMaxToxProb'
.DefaultIncrementsMin	'IncrementsMin'
.DefaultIncrementsOrdinal	'IncrementsOrdinal'
.DefaultIncrementsRelative	'IncrementsRelative'
.DefaultIncrementsRelativeDLT	'IncrementsRelativeDLT'
.DefaultIncrementsRelativeDLTCurrent	'IncrementsRelativeDLTCurrent'
.DefaultIncrementsRelativeParts	'IncrementsRelativeParts'
.DefaultLogisticIndepBeta	'LogisticIndepBeta'
.DefaultLogisticKadane	'LogisticKadane'
.DefaultLogisticKadaneBetaGamma	'LogisticKadaneBetaGamma'
.DefaultLogisticLogNormal	'LogisticLogNormal'
.DefaultLogisticLogNormalGrouped	'LogisticLogNormalGrouped'
.DefaultLogisticLogNormalMixture	'LogisticLogNormalMixture'
.DefaultLogisticLogNormalOrdinal	'LogisticLogNormalOrdinal'
.DefaultLogisticLogNormalSub	'LogisticLogNormalSub'
.DefaultLogisticNormal	'LogisticNormal'
.DefaultLogisticNormalFixedMixture	'LogisticNormalFixedMixture'
.DefaultLogisticNormalMixture	'LogisticNormalMixture'
.DefaultMcmcOptions	'McmcOptions'
.DefaultModelEff	'ModelEff'
.DefaultModelLogNormal	'ModelLogNormal'
.DefaultModelParamsNormal	'ModelParamsNormal'
.DefaultModelPseudo	'ModelPseudo'
.DefaultModelTox	'ModelTox'
.DefaultNextBest	'NextBest'
.DefaultNextBestDualEndpoint	'NextBestDualEndpoint'
.DefaultNextBestEWOC	'NextBestEWOC'
.DefaultNextBestInfTheory	'NextBestInfTheory'
.DefaultNextBestMaxGain	'NextBestMaxGain'
.DefaultNextBestMaxGainSamples	'NextBestMaxGainSamples'
.DefaultNextBestMinDist	'NextBestMinDist'
.DefaultNextBestMTD	'NextBestMTD'
.DefaultNextBestNCRM	'NextBestNCRM'
.DefaultNextBestNCRMLoss	'NextBestNCRMLoss'
.DefaultNextBestOrdinal	'NextBestOrdinal'
.DefaultNextBestProbMTDLTE	'NextBestProbMTDLTE'
.DefaultNextBestProbMTDMinDist	'NextBestProbMTDMinDist'
.DefaultNextBestTD	'NextBestTD'
.DefaultNextBestTDsamples	'NextBestTDsamples'
.DefaultNextBestThreePlusThree	'NextBestThreePlusThree'
.DefaultOneParExpPrior	'OneParExpPrior'
.DefaultOneParLogNormalPrior	'OneParLogNormalPrior'
.DefaultProbitLogNormal	'ProbitLogNormal'
.DefaultProbitLogNormalRel	'ProbitLogNormalRel'
.DefaultPseudoDualFlexiSimulations	'PseudoDualFlexiSimulations'
.DefaultPseudoDualSimulations	'PseudoDualSimulations'
.DefaultPseudoDualSimulationsSummary	'PseudoDualSimulationsSummary'
.DefaultPseudoSimulations	'PseudoSimulations'
.DefaultPseudoSimulationsSummary	'PseudoSimulationsSummary'
.DefaultRuleDesign	'RuleDesign'
.DefaultRuleDesignOrdinal	'RuleDesignOrdinal'
.DefaultSafetyWindow	'SafetyWindow'
.DefaultSafetyWindowConst	'SafetyWindowConst'
.DefaultSafetyWindowSize	'SafetyWindowSize'
.DefaultSamples	'Samples'
.DefaultSimulations	'Simulations'
.DefaultSimulationsSummary	'SimulationsSummary'
.DefaultStoppingAll	'StoppingAll'
.DefaultStoppingAny	'StoppingAny'
.DefaultStoppingCohortsNearDose	'StoppingCohortsNearDose'
.DefaultStoppingExternal	'StoppingExternal'
.DefaultStoppingHighestDose	'StoppingHighestDose'
.DefaultStoppingList	'StoppingList'
.DefaultStoppingLowestDoseHSRBeta	'StoppingLowestDoseHSRBeta'
.DefaultStoppingMaxGainCIRatio	'StoppingMaxGainCIRatio'
.DefaultStoppingMinCohorts	'StoppingMinCohorts'
.DefaultStoppingMinPatients	'StoppingMinPatients'
.DefaultStoppingMissingDose	'StoppingMissingDose'
.DefaultStoppingMTDCV	'StoppingMTDCV'
.DefaultStoppingMTDdistribution	'StoppingMTDdistribution'
.DefaultStoppingOrdinal	'StoppingOrdinal'
.DefaultStoppingPatientsNearDose	'StoppingPatientsNearDose'
.DefaultStoppingSpecificDose	'StoppingSpecificDose'
.DefaultStoppingTargetBiomarker	'StoppingTargetBiomarker'
.DefaultStoppingTargetProb	'StoppingTargetProb'
.DefaultStoppingTDCIRatio	'StoppingTDCIRatio'
.DefaultTDDesign	'TDDesign'
.DefaultTDsamplesDesign	'TDsamplesDesign'
.DefaultTITELogisticLogNormal	'TITELogisticLogNormal'
.Design	'Design'
.DesignGrouped	'DesignGrouped'
.DesignOrdinal	'DesignOrdinal'
.DualDesign	'DualDesign'
.DualEndpoint	'DualEndpoint'
.DualEndpointBeta	'DualEndpointBeta'
.DualEndpointEmax	'DualEndpointEmax'
.DualEndpointRW	'DualEndpointRW'
.DualResponsesDesign	'DualResponsesDesign.R'
.DualResponsesSamplesDesign	'DualResponsesSamplesDesign'
.DualSimulations	'DualSimulations'
.DualSimulationsSummary	'DualSimulationsSummary'
.EffFlexi	'EffFlexi'
.Effloglog	'Effloglog'
.FractionalCRM	'FractionalCRM'
.GeneralData	'GeneralData'
.GeneralModel	'GeneralModel'
.GeneralSimulations	'GeneralSimulations'
.GeneralSimulationsSummary	'GeneralSimulationsSummary'
.IncrementsDoseLevels	'IncrementsDoseLevels'
.IncrementsHSRBeta	'IncrementsHSRBeta'
.IncrementsMaxToxProb	'IncrementsMaxToxProb'
.IncrementsMin	'IncrementsMin'
.IncrementsOrdinal	'IncrementsOrdinal'
.IncrementsRelative	'IncrementsRelative'
.IncrementsRelativeDLT	'IncrementsRelativeDLT'
.IncrementsRelativeDLTCurrent	'IncrementsRelativeDLTCurrent'
.IncrementsRelativeParts	'IncrementsRelativeParts'
.LogisticIndepBeta	'LogisticIndepBeta'
.LogisticKadane	'LogisticKadane'
.LogisticKadaneBetaGamma	'LogisticKadaneBetaGamma'
.LogisticLogNormal	'LogisticLogNormal'
.LogisticLogNormalGrouped	'LogisticLogNormalGrouped'
.LogisticLogNormalMixture	'LogisticLogNormalMixture'
.LogisticLogNormalOrdinal	'LogisticLogNormalOrdinal'
.LogisticLogNormalSub	'LogisticLogNormalSub'
.LogisticNormal	'LogisticNormal'
.LogisticNormalFixedMixture	'LogisticNormalFixedMixture'
.LogisticNormalMixture	'LogisticNormalMixture'
.McmcOptions	'McmcOptions'
.ModelEff	'ModelEff'
.ModelLogNormal	'ModelLogNormal'
.ModelParamsNormal	'ModelParamsNormal'
.ModelPseudo	'ModelPseudo'
.ModelTox	'ModelTox'
.NextBestDualEndpoint	'NextBestDualEndpoint'
.NextBestEWOC	'NextBestEWOC'
.NextBestInfTheory	'NextBestInfTheory'
.NextBestMaxGain	'NextBestMaxGain'
.NextBestMaxGainSamples	'NextBestMaxGainSamples'
.NextBestMinDist	'NextBestMinDist'
.NextBestMTD	'NextBestMTD'
.NextBestNCRM	'NextBestNCRM'
.NextBestNCRMLoss	'NextBestNCRMLoss'
.NextBestOrdinal	'NextBestOrdinal'
.NextBestProbMTDLTE	'NextBestProbMTDLTE'
.NextBestProbMTDMinDist	'NextBestProbMTDMinDist'
.NextBestTD	'NextBestTD'
.NextBestTDsamples	'NextBestTDsamples'
.NextBestThreePlusThree	'NextBestThreePlusThree'
.OneParExpPrior	'OneParExpPrior'
.OneParLogNormalPrior	'OneParLogNormalPrior'
.ProbitLogNormal	'ProbitLogNormal'
.ProbitLogNormalRel	'ProbitLogNormalRel'
.PseudoDualFlexiSimulations	'PseudoDualFlexiSimulations'
.PseudoDualSimulations	'PseudoDualSimulations'
.PseudoDualSimulationsSummary	'PseudoDualSimulationsSummary'
.PseudoSimulations	'PseudoSimulations'
.PseudoSimulationsSummary	'PseudoSimulationsSummary'
.RuleDesign	'RuleDesign'
.RuleDesignOrdinal	'RuleDesignOrdinal'
.SafetyWindowConst	'SafetyWindowConst'
.SafetyWindowSize	'SafetyWindowSize'
.Samples	'Samples'
.Simulations	'Simulations'
.SimulationsSummary	'SimulationsSummary'
.StoppingAll	'StoppingAll'
.StoppingAny	'StoppingAny'
.StoppingCohortsNearDose	'StoppingCohortsNearDose'
.StoppingExternal	'StoppingExternal'
.StoppingHighestDose	'StoppingHighestDose'
.StoppingList	'StoppingList'
.StoppingLowestDoseHSRBeta	'StoppingLowestDoseHSRBeta'
.StoppingMaxGainCIRatio	'StoppingMaxGainCIRatio'
.StoppingMinCohorts	'StoppingMinCohorts'
.StoppingMinPatients	'StoppingMinPatients'
.StoppingMissingDose	'StoppingMissingDose'
.StoppingMTDCV	'StoppingMTDCV'
.StoppingMTDdistribution	'StoppingMTDdistribution'
.StoppingOrdinal	'StoppingOrdinal'
.StoppingPatientsNearDose	'StoppingPatientsNearDose'
.StoppingSpecificDose	'StoppingSpecificDose'
.StoppingTargetBiomarker	'StoppingTargetBiomarker'
.StoppingTargetProb	'StoppingTargetProb'
.StoppingTDCIRatio	'StoppingTDCIRatio'
.TDDesign	'TDDesign'
.TDsamplesDesign	'TDsamplesDesign'
.TITELogisticLogNormal	'TITELogisticLogNormal'
|-method	Combine Two Stopping Rules with OR
|-method	Combine an Atomic Stopping Rule and a Stopping List with OR
|-method	Combine a Stopping List and an Atomic Stopping Rule with OR