R/Simulations-class.R
In 0liver0815/onc-crmpack-test: Object-Oriented Implementation of CRM Designs
Defines functions
DASimulations
PseudoDualFlexiSimulations
PseudoDualSimulations
PseudoSimulations
DualSimulations
Simulations
GeneralSimulations
Documented in
DASimulations
DualSimulations
GeneralSimulations
PseudoDualFlexiSimulations
PseudoDualSimulations
PseudoSimulations
Simulations
#####################################################################################
## Author: Daniel Sabanes Bove [sabanesd *a*t* roche *.* com]
## Wai Yin Yeung [w *.* yeung1 *a*t* lancaster *.* ac *.* uk]
## Project: Object-oriented implementation of CRM designs
##
## Time-stamp: <[Simulations-class.R] by DSB Sam 17/01/2015 19:42>
##
## Description:
## Encapsulate the simulations output in a formal class.
##
## History:
## 12/02/2014 file creation
## 10/07/2015 added Pseudo simulation class
###################################################################################
##' @include helpers.R
##' @include Data-class.R
{}
##' General class for the simulations output
##'
##' This class captures trial simulations.
##'
##' Here also the random generator state before starting the simulation is
##' saved, in order to be able to reproduce the outcome. For this just use
##' \code{\link{set.seed}} with the \code{seed} as argument before running
##' \code{\link{simulate,Design-method}}.
##'
##' @slot data list of produced \code{\linkS4class{Data}} objects
##' @slot doses the vector of final dose recommendations
##' @slot seed random generator state before starting the simulation
##'
##' @export
##' @keywords classes
.GeneralSimulations <-
setClass(Class="GeneralSimulations",
representation(data="list",
doses="numeric",
seed="integer"),
prototype(data=
list(Data(x=1:2,
y=0:1,
doseGrid=1:2),
Data(x=3:4,
y=0:1,
doseGrid=3:4)),
doses=c(1, 2),
seed=1L),
validity=
function(object){
o <- Validate()
nSims <- length(object@data)
o$check(all(sapply(object@data, is, "Data")),
"all data elements must be Data objects")
o$check(identical(length(object@doses), nSims),
"doses must have same length as the data list")
o$result()
})
validObject(.GeneralSimulations())
##' Initialization function for "GeneralSimulations"
##'
##' @param data see \code{\linkS4class{GeneralSimulations}}
##' @param doses see \code{\linkS4class{GeneralSimulations}}
##' @param seed see \code{\linkS4class{GeneralSimulations}}
##' @return the \code{\linkS4class{GeneralSimulations}} object
##'
##' @export
##' @keywords methods
GeneralSimulations <- function(data,
doses,
seed)
{
.GeneralSimulations(data=data,
doses=doses,
seed=safeInteger(seed))
}
##' Class for the simulations output from model based designs
##'
##' This class captures the trial simulations from model based designs.
##' Additional slots fit and stopReasons compared to the general class
##' \code{\linkS4class{GeneralSimulations}}.
##'
##' @slot fit list with the final fits
##' @slot stopReasons list of stopping reasons for each simulation run
##'
##' @export
##' @keywords classes
.Simulations <-
setClass(Class="Simulations",
representation(fit="list",
stopReasons="list"),
## note: this prototype is put together with the prototype
## for GeneralSimulations
prototype(fit=
list(c(0.1, 0.2),
c(0.1, 0.2)),
stopReasons=
list("A", "A")),
contains="GeneralSimulations",
validity=
function(object){
o <- Validate()
nSims <- length(object@data)
o$check(identical(length(object@fit), nSims),
"fit must have same length as data")
o$check(identical(length(object@stopReasons), nSims),
"stopReasons must have same length as data")
o$result()
})
validObject(.Simulations())
##' Initialization function for the "Simulations" class
##'
##' @param fit see \code{\linkS4class{Simulations}}
##' @param stopReasons see \code{\linkS4class{Simulations}}
##' @param \dots additional parameters from \code{\link{GeneralSimulations}}
##' @return the \code{\linkS4class{Simulations}} object
##' @export
##'
##' @keywords methods
Simulations <- function(fit,
stopReasons,
...)
{
start <- GeneralSimulations(...)
.Simulations(start,
fit=fit,
stopReasons=stopReasons)
}
##' Class for the simulations output from dual-endpoint model based designs
##'
##' This class captures the trial simulations from dual-endpoint model based
##' designs. In comparison to the parent class \code{\linkS4class{Simulations}},
##' it contains additional slots to capture the dose-biomarker fits, and the
##' sigma2W and rho estimates.
##'
##' @slot rhoEst the vector of final posterior median rho estimates
##' @slot sigma2West the vector of final posterior median sigma2W estimates
##' @slot fitBiomarker list with the final dose-biomarker curve fits
##'
##' @export
##' @keywords classes
.DualSimulations <-
setClass(Class="DualSimulations",
representation(rhoEst="numeric",
sigma2West="numeric",
fitBiomarker="list"),
prototype(rhoEst=c(0.2, 0.3),
sigma2West=c(0.2, 0.3),
fitBiomarker=
list(c(0.1, 0.2),
c(0.1, 0.2))),
contains="Simulations",
validity=
function(object){
o <- Validate()
nSims <- length(object@data)
o$check(identical(length(object@fitBiomarker), nSims),
"fitBiomarker list has to have same length as data")
o$check(identical(length(object@rhoEst), nSims),
"rhoEst vector has to have same length as data")
o$check(identical(length(object@sigma2West), nSims),
"sigma2West has to have same length as data")
o$result()
})
validObject(.DualSimulations())
##' Initialization function for "DualSimulations"
##'
##' @param rhoEst see \code{\linkS4class{DualSimulations}}
##' @param sigma2West see \code{\linkS4class{DualSimulations}}
##' @param fitBiomarker see \code{\linkS4class{DualSimulations}}
##' @param \dots additional parameters from \code{\link{Simulations}}
##' @return the \code{\linkS4class{DualSimulations}} object
##'
##' @export
##' @keywords methods
DualSimulations <- function(rhoEst,
sigma2West,
fitBiomarker,
...)
{
start <- Simulations(...)
.DualSimulations(start,
rhoEst=rhoEst,
sigma2West=sigma2West,
fitBiomarker=fitBiomarker)
}
##' Class for the summary of general simulations output
##'
##' Note that objects should not be created by users, therefore no
##' initialization function is provided for this class.
##'
##' @slot target target toxicity interval
##' @slot targetDoseInterval corresponding target dose interval
##' @slot nsim number of simulations
##' @slot propDLTs proportions of DLTs in the trials
##' @slot meanToxRisk mean toxicity risks for the patients
##' @slot doseSelected doses selected as MTD
##' @slot toxAtDosesSelected true toxicity at doses selected
##' @slot propAtTarget Proportion of trials selecting target MTD
##' @slot doseMostSelected dose most often selected as MTD
##' @slot obsToxRateAtDoseMostSelected observed toxicity rate at dose most often
##' selected
##' @slot nObs number of patients overall
##' @slot nAboveTarget number of patients treated above target tox interval
##' @slot doseGrid the dose grid that has been used
##' @slot placebo set to TRUE (default is FALSE) for a design with placebo
##'
##' @export
##' @keywords classes
.GeneralSimulationsSummary <-
setClass(Class="GeneralSimulationsSummary",
representation(target="numeric",
targetDoseInterval="numeric",
nsim="integer",
propDLTs="ANY",
meanToxRisk="numeric",
doseSelected="numeric",
toxAtDosesSelected="numeric",
propAtTarget="numeric",
doseMostSelected="numeric",
obsToxRateAtDoseMostSelected="numeric",
nObs="ANY",
nAboveTarget="integer",
doseGrid="numeric",
placebo="logical"))
##' Class for the summary of model-based simulations output
##'
##' In addition to the slots in the parent class
##' \code{\linkS4class{GeneralSimulationsSummary}}, it contains two slots with
##' model fit information.
##'
##' Note that objects should not be created by users, therefore no
##' initialization function is provided for this class.
##'
##' @slot fitAtDoseMostSelected fitted toxicity rate at dose most often selected
##' @slot meanFit list with the average, lower (2.5%) and upper (97.5%)
##' quantiles of the mean fitted toxicity at each dose level
##'
##' @export
##' @keywords classes
.SimulationsSummary <-
setClass(Class="SimulationsSummary",
representation(fitAtDoseMostSelected="numeric",
meanFit="list"),
contains="GeneralSimulationsSummary")
##' Class for the summary of dual-endpoint simulations output
##'
##' In addition to the slots in the parent class
##' \code{\linkS4class{SimulationsSummary}}, it contains two slots for the
##' biomarker model fit information.
##'
##' Note that objects should not be created by users, therefore no
##' initialization function is provided for this class.
##'
##' @slot biomarkerFitAtDoseMostSelected fitted biomarker level at dose most often selected
##' @slot meanBiomarkerFit list with the average, lower (2.5%) and upper (97.5%)
##' quantiles of the mean fitted biomarker level at each dose level
##'
##' @export
##' @keywords classes
.DualSimulationsSummary <-
setClass(Class="DualSimulationsSummary",
contains="SimulationsSummary",
representation=
representation(biomarkerFitAtDoseMostSelected="numeric",
meanBiomarkerFit="list"))
## ==============================================================================
## -------------------------------------------------------------------------------
## class for simulation using pseudo models
## ------------------------------------------------------------------------
##' Class `PseudoSimulations`
##'
##' This is a class which captures the trial simulations from designs using
##' pseudo model. The design for DLE only responses and model from \code{\linkS4class{ModelTox}}
##' class object. It contains all slots from \code{\linkS4class{GeneralSimulations}} object.
##' Additional slots fit and stopReasons compared to the general class
##' \code{\linkS4class{GeneralSimulations}}.
##'
##' @slot fit list of the final values. If samples are involved, these are the final fitted values.
##' If no samples are involved, these are included the final modal estimates of the model parameters
##' and the posterior estimates of the probabilities of the occurrence of a DLE.
##' @slot FinalTDtargetDuringTrialEstimates the vector of all final estimates (the last estimate of) the TDtargetDuringTrial at the end
##' of each simulations/when each trial stops
##' @slot FinalTDtargetEndOfTrialEstimates vector of all final estimates or the last estimate of the TDtargetEndOfTrial when each trial
##' stops
##' @slot FinalTDtargetDuringTrialAtDoseGrid vector of the dose levels at dose grid closest below the final TDtargetDuringTrial estimates
##' @slot FinalTDtargetEndOfTrialAtDoseGrid vector of the dose levels at dose grid closest below the final TDtargetEndOfTrial estimates
##' @slot FinalTDEOTCIs is the list of all 95% credibility interval of the final estimates of the TDtargetEndOfTrial
##' @slot FinalTDEOTRatios is the vector of the ratios of the CI, the ratio of the upper to the lower 95% credibility intervals
##' of the final estimates of the TDtargetEndOfTrial
##' @slot FinalCIs list of all the final 95% credibility intervals of the TDtargetEndofTrial estimates or of the final optimal dose
##' estimates when DLE and efficacy responses are incorporated after each simulations
##' @slot FinalRatios vector of all the final ratios, the ratios of the upper to the lower 95% credibility interval of the
##' final estimates of the TDtargetEndOfTrial or of the final optimal dose estimates (when DLE and efficacy responses are
##' incorporated) after each simulations
##' @slot stopReasons add slot description
##'
##' @export
.PseudoSimulations <-
setClass(Class="PseudoSimulations",
representation(fit="list",
FinalTDtargetDuringTrialEstimates="numeric",
FinalTDtargetEndOfTrialEstimates = "numeric",
FinalTDtargetDuringTrialAtDoseGrid="numeric",
FinalTDtargetEndOfTrialAtDoseGrid ="numeric",
FinalTDEOTCIs="list",
FinalTDEOTRatios="numeric",
FinalCIs="list",
FinalRatios="numeric",
stopReasons="list"),
## note: this prototype is put together with the prototype
## for GeneralSimulations
prototype(FinalTDtargetDuringTrialEstimates= c(0.1,0.1),
FinalTDtargetEndOfTrialEstimates=c(0.1,0.1),
FinalTDtargetDuringTrialAtDoseGrid=c(0.1,0.1),
FinalTDtargetEndOfTrialAtDoseGrid=c(0.1,0.1),
FinalTDEOTCIs=list(c(0.1, 0.2),c(0.1, 0.2)),
FinalTDEOTRatios=c(0.1,0.1),
FinalCIs=list(c(0.1, 0.2),c(0.1, 0.2)),
FinalRatios=c(0.1,0.1),
stopReasons=
list("A", "A")),
contains="GeneralSimulations",
validity=
function(object){
o <- Validate()
nSims <- length(object@data)
o$check(identical(length(object@stopReasons), nSims),
"stopReasons must have same length as data")
o$result()
})
validObject(.PseudoSimulations())
##' Initialization function of the 'PseudoSimulations' class
##' @param fit please refer to \code{\linkS4class{PseudoSimulations}} class object
##' @param FinalTDtargetDuringTrialEstimates please refer to \code{\linkS4class{PseudoSimulations}} class object
##' @param FinalTDtargetEndOfTrialEstimates please refer to \code{\linkS4class{PseudoSimulations}} class object
##' @param FinalTDtargetDuringTrialAtDoseGrid please refer to \code{\linkS4class{PseudoSimulations}} class object
##' @param FinalTDtargetEndOfTrialAtDoseGrid please refer to \code{\linkS4class{PseudoSimulations}} class object
##' @param FinalTDEOTCIs please refer to \code{\linkS4class{PseudoSimulations}} class object
##' @param FinalTDEOTRatios please refer to \code{\linkS4class{PseudoSimulations}} class object
##' @param FinalCIs please refer to \code{\linkS4class{PseudoSimulations}} class object
##' @param FinalRatios please refer to \code{\linkS4class{PseudoSimulations}} class object
##' @param stopReasons please refer to \code{\linkS4class{PseudoSimulations}} class object
##' @param \dots additional parameters from \code{\linkS4class{GeneralSimulations}}
##' @return the \code{\linkS4class{PseudoSimulations}} object
##'
##' @export
PseudoSimulations <- function(fit,
FinalTDtargetDuringTrialEstimates,
FinalTDtargetEndOfTrialEstimates,
FinalTDtargetDuringTrialAtDoseGrid,
FinalTDtargetEndOfTrialAtDoseGrid,
FinalTDEOTCIs,
FinalTDEOTRatios,
FinalCIs,
FinalRatios,
stopReasons,
...)
{
start <- GeneralSimulations(...)
.PseudoSimulations(start,
fit=fit,
FinalTDtargetDuringTrialEstimates=FinalTDtargetDuringTrialEstimates,
FinalTDtargetEndOfTrialEstimates=FinalTDtargetEndOfTrialEstimates,
FinalTDtargetDuringTrialAtDoseGrid=FinalTDtargetDuringTrialAtDoseGrid,
FinalTDtargetEndOfTrialAtDoseGrid= FinalTDtargetEndOfTrialAtDoseGrid,
FinalTDEOTCIs=FinalTDEOTCIs,
FinalTDEOTRatios=FinalTDEOTRatios,
FinalCIs=FinalCIs,
FinalRatios=FinalRatios,
stopReasons=stopReasons)
}
## ===============================================================================
## -------------------------------------------------------------------------------
## Class for Pseudo simulation using DLE and efficacy responses (Pseudo models except 'EffFlexi' model)
## -----------------------------------------------------------------------------------
##' Class `PseudoDualSimulations`
##'
##' This is a class which captures the trial simulations design using both the
##' DLE and efficacy responses. The design of model from \code{\linkS4class{ModelTox}}
##' class and the efficacy model from \code{\linkS4class{ModelEff}} class
##' (except \code{\linkS4class{EffFlexi}} class). It contains all slots from
##' \code{\linkS4class{GeneralSimulations}} and \code{\linkS4class{PseudoSimulations}} object.
##' In comparison to the parent class \code{\linkS4class{PseudoSimulations}},
##' it contains additional slots to
##' capture the dose-efficacy curve and the sigma2 estimates.
##'
##' @slot fitEff list of the final values. If DLE and efficacy samples are generated, it contains the
##' final fitted values. If no DLE and efficacy samples are used, it contains the modal estimates of the
##' parameters in the two models and the posterior estimates of the probabilities of the occurrence of a
##' DLE and the expected efficacy responses.
##' @slot FinalGstarEstimates a vector of the final estimates of Gstar at the end of each simulations.
##' @slot FinalGstarAtDoseGrid is a vector of the final estimates of Gstar at dose Grid at the end of each simulations
##' @slot FinalGstarCIs is the list of all 95% credibility interval of the final estimates of Gstar
##' @slot FinalGstarRatios is the vector of the ratios of the CI, the ratio of the upper to the lower 95% credibility interval
##' of the final estimates of Gstar
##' @slot FinalOptimalDose is the vector of the final optimal dose, the minimum of the final TDtargetEndOfTrial estimates and Gstar
##' estimates
##' @slot FinalOptimalDoseAtDoseGrid is the vector of the final optimal dose, the minimum of the final TDtargetEndOfTrial estimates
##' and Gstar estimates at dose Grid
##' @slot sigma2est the vector of the final posterior mean sigma2 estimates
##'
##' @export
.PseudoDualSimulations <-
setClass(Class="PseudoDualSimulations",
representation(fitEff="list",
FinalGstarEstimates="numeric",
FinalGstarAtDoseGrid="numeric",
FinalGstarCIs="list",
FinalGstarRatios="numeric",
FinalOptimalDose="numeric",
FinalOptimalDoseAtDoseGrid="numeric",
sigma2est="numeric"),
prototype( FinalGstarEstimates=c(0.1,0.1),
FinalGstarAtDoseGrid=c(0.1,0.1),
FinalGstarCIs=list(c(0.1, 0.2),
c(0.1, 0.2)),
FinalGstarRatios=c(0.01,0.01),
FinalOptimalDose=c(0.01,0.01),
FinalOptimalDoseAtDoseGrid=c(0.01,0.01),
sigma2est= c(0.001,0.002)),
contains="PseudoSimulations",
validity=
function(object){
o <- Validate()
nSims <- length(object@data)
o$check(identical(length(object@sigma2est),nSims),
"sigma2est has to have same length as data")
o$result()
})
validObject(.PseudoDualSimulations())
##' Initialization function for 'DualPseudoSimulations' class
##' @param fitEff please refer to \code{\linkS4class{PseudoDualSimulations}} class object
##' @param FinalGstarEstimates please refer to \code{\linkS4class{PseudoDualSimulations}} class object
##' @param FinalGstarAtDoseGrid please refer to \code{\linkS4class{PseudoDualSimulations}} class object
##' @param FinalGstarCIs please refer to \code{\linkS4class{PseudoDualSimulations}} class object
##' @param FinalGstarRatios please refer to \code{\linkS4class{PseudoDualSimulations}} class object
##' @param FinalOptimalDose please refer to \code{\linkS4class{PseudoDualSimulations}} class object
##' @param FinalOptimalDoseAtDoseGrid please refer to \code{\linkS4class{PseudoDualSimulations}} class object
##' @param sigma2est please refer to \code{\linkS4class{PseudoDualSimulations}} class object
##' @param \dots additional parameters from \code{\linkS4class{PseudoSimulations}}
##' @return the \code{\linkS4class{PseudoDualSimulations}} object
PseudoDualSimulations <- function(fitEff,
FinalGstarEstimates,
FinalGstarAtDoseGrid,
FinalGstarCIs,
FinalGstarRatios,
FinalOptimalDose,
FinalOptimalDoseAtDoseGrid,
sigma2est,
...)
{
start <- PseudoSimulations(...)
.PseudoDualSimulations(start,
fitEff=fitEff,
FinalGstarEstimates=FinalGstarEstimates,
FinalGstarAtDoseGrid=FinalGstarAtDoseGrid,
FinalGstarCIs=FinalGstarCIs,
FinalGstarRatios=FinalGstarRatios,
FinalOptimalDose=FinalOptimalDose,
FinalOptimalDoseAtDoseGrid=FinalOptimalDoseAtDoseGrid,
sigma2est=sigma2est)
}
## -------------------------------------------------------------------------------
## Class for Pseudo simulation using DLE and efficacy responses using 'EffFlex' efficacy model
## -----------------------------------------------------------------------------------
##' This is a class which captures the trial simulations design using both the
##' DLE and efficacy responses. The design of model from \code{\linkS4class{ModelTox}}
##' class and the efficacy model from \code{\linkS4class{EffFlexi}} class
##' It contains all slots from
##' \code{\linkS4class{GeneralSimulations}}, \code{\linkS4class{PseudoSimulations}}
##' and \code{\linkS4class{PseudoDualSimulations}} object.
##' In comparison to the parent class \code{\linkS4class{PseudoDualSimulations}},
##' it contains additional slots to
##' capture the sigma2betaW estimates.
##'
##' @slot sigma2betaWest the vector of the final posterior mean sigma2betaW estimates
##'
##' @export
##' @keywords class
.PseudoDualFlexiSimulations <-
setClass(Class="PseudoDualFlexiSimulations",
representation(sigma2betaWest="numeric"),
prototype(sigma2betaWest= c(0.001,0.002)),
contains="PseudoDualSimulations",
validity=
function(object){
o <- Validate()
nSims <- length(object@data)
o$check(identical(length(object@sigma2betaWest),nSims),
"sigma2betaWest has to have same length as data")
o$result()
})
validObject(.PseudoDualFlexiSimulations())
##' Initialization function for 'PseudoDualFlexiSimulations' class
##' @param sigma2betaWest please refer to \code{\linkS4class{PseudoDualFlexiSimulations}} class object
##' @param \dots additional parameters from \code{\linkS4class{PseudoDualSimulations}}
##' @return the \code{\linkS4class{PseudoDualFlexiSimulations}} object
PseudoDualFlexiSimulations <- function(sigma2betaWest,
...)
{
start <- PseudoDualSimulations(...)
.PseudoDualFlexiSimulations(start,
sigma2betaWest=sigma2betaWest)
}
## -------------------------------------------------------------------------------------------------------
## ================================================================================================
##' Class for the summary of pseudo-models simulations output
##'
##' Note that objects should not be created by users, therefore no
##' initialization function is provided for this class.
##'
##' @slot targetEndOfTrial the target probability of DLE wanted at the end of a trial
##' @slot targetDoseEndOfTrial the dose level corresponds to the target probability
##' of DLE wanted at the end of a trial, TDEOT
##' @slot targetDoseEndOfTrialAtDoseGrid the dose level at dose grid corresponds to the target probability
##' of DLE wanted at the end of a trial
##' @slot targetDuringTrial the target probability of DLE wanted during a trial
##' @slot targetDoseDuringTrial the dose level corresponds to the target probability of DLE
##' wanted during the trial. TDDT
##' @slot targetDoseDuringTrialAtDoseGrid the dose level at dose grid corresponds to the target probability
##' of DLE wanted during a trial
##' @slot TDEOTSummary the six-number table summary, include the lowest, the 25th precentile (lower quartile),
##' the 50th percentile (median), the mean, the 27th percentile and the highest values of the
##' final dose levels obtained corresponds to the target probability of DLE
##' want at the end of a trial across all simulations
##' @slot TDDTSummary the six-number table summary, include the lowest, the 25th precentile (lower quartile),
##' the 50th percentile (median), the mean, the 27th percentile and the highest values of the
##' final dose levels obtained corresponds to the target probability of DLE
##' want during a trial across all simulations
##' @slot FinalDoseRecSummary the six-number table summary, include the lowest, the 25th precentile (lower quartile),
##' the 50th percentile (median), the mean, the 27th percentile and the highest values of the
##' final optimal doses, which is either the TDEOT when only DLE response are incorporated into
##' the escalation procedure or the minimum of the TDEOT and Gstar when DLE and efficacy responses are
##' incorporated, across all simulations
##' @slot ratioTDEOTSummary the six-number summary table of the final ratios of the upper to the lower 95%
##' credibility intervals of the final TDEOTs across all simulations
##' @slot FinalRatioSummary the six-number summary table of the final ratios of the upper to the lower 95%
##' credibility intervals of the final optimal doses across all simulations
##' #@slot doseRec the dose level that will be recommend for subsequent study
##' @slot nsim number of simulations
##' @slot propDLE proportions of DLE in the trials
##' @slot meanToxRisk mean toxicity risks for the patients
##' @slot doseSelected doses selected as MTD (targetDoseEndOfTrial)
##' @slot toxAtDosesSelected true toxicity at doses selected
##' @slot propAtTargetEndOfTrial Proportion of trials selecting at the doseGrid closest below the MTD, the
##' targetDoseEndOfTrial
##' @slot propAtTargetDuringTrial Proportion of trials selecting at the doseGrid closest below the
##' targetDoseDuringTrial
##' @slot doseMostSelected dose most often selected as MTD
##' @slot obsToxRateAtDoseMostSelected observed toxicity rate at dose most often
##' selected
##' @slot nObs number of patients overall
##' @slot nAboveTargetEndOfTrial number of patients treated above targetDoseEndOfTrial
##' @slot nAboveTargetDuringTrial number of patients treated above targetDoseDuringTrial
##' @slot doseGrid the dose grid that has been used
##' @slot fitAtDoseMostSelected fitted toxicity rate at dose most often selected
##' @slot meanFit list with the average, lower (2.5%) and upper (97.5%)
##' quantiles of the mean fitted toxicity at each dose level
##'
##'
##' @export
##' @keywords classes
.PseudoSimulationsSummary <-
setClass(Class="PseudoSimulationsSummary",
representation(targetEndOfTrial="numeric",
targetDoseEndOfTrial="numeric",
targetDoseEndOfTrialAtDoseGrid="numeric",
targetDuringTrial="numeric",
targetDoseDuringTrial="numeric",
targetDoseDuringTrialAtDoseGrid="numeric",
TDEOTSummary="table",
TDDTSummary="table",
FinalDoseRecSummary="table",
ratioTDEOTSummary="table",
FinalRatioSummary="table",
#doseRec="numeric",
nsim="integer",
propDLE="numeric",
meanToxRisk="numeric",
doseSelected="numeric",
toxAtDosesSelected="numeric",
propAtTargetEndOfTrial="numeric",
propAtTargetDuringTrial="numeric",
doseMostSelected="numeric",
obsToxRateAtDoseMostSelected="numeric",
nObs="integer",
nAboveTargetEndOfTrial="integer",
nAboveTargetDuringTrial="integer",
doseGrid="numeric",
fitAtDoseMostSelected="numeric",
meanFit="list"))
## ---------------------------------------------------------------------------------------------
##' Class for the summary of the dual responses simulations using pseudo models
##'
##' It contains all slots from \code{\linkS4class{PseudoSimulationsSummary}} object. In addition to
##' the slots in the parent class \code{\linkS4class{PseudoSimulationsSummary}}, it contains four
##' more slots for the efficacy model fit information.
##'
##' Note that objects should not be created by users, therefore no initialization function
##' is provided for this class.
##'
##' @slot targetGstar the target dose level such that its gain value is at maximum
##' @slot targetGstarAtDoseGrid the dose level at dose Grid closest and below Gstar
##' @slot GstarSummary the six-number table summary (lowest, 25th, 50th (median), 75th percentile, mean
##' and highest value) of the final Gstar values obtained across all simulations
##' @slot ratioGstarSummary the six-number summary table of the ratios of the upper to the lower 95%
##' credibility intervals of the final Gstar across all simulations
##' @slot EffFitAtDoseMostSelected fitted expected mean efficacy value at dose most often
##' selected
##' @slot meanEffFit list with mean, lower (2.5%) and upper (97.5%) quantiles of the fitted expected
##' efficacy value at each dose level.
##'
##' @export
##' @keywords class
.PseudoDualSimulationsSummary <-
setClass(Class="PseudoDualSimulationsSummary",
contains="PseudoSimulationsSummary",
representation=
representation(targetGstar="numeric",
targetGstarAtDoseGrid="numeric",
GstarSummary="table",
ratioGstarSummary="table",
EffFitAtDoseMostSelected="numeric",
meanEffFit="list"))
## ---------------------------------------------------------------------------------------------
##' Class for the simulations output from DA based designs
##'
##' This class captures the trial simulations from DA based
##' designs. In comparison to the parent class \code{\linkS4class{Simulations}},
##' it contains additional slots to capture the time to DLT fits, additional
##' parameters and the trial duration.
##'
##' @slot trialduration the vector of trial duration values for all simulations.
##'
##' @export
##' @keywords classes
.DASimulations <-
setClass(Class="DASimulations",
representation(trialduration="numeric"),
prototype(trialduration=rep(0,2)),
contains="Simulations",
validity=
function(object){
o <- Validate()
nSims <- length(object@data)
o$check(identical(length(object@trialduration), nSims),
"trialduration vector has to have same length as data")
o$result()
})
validObject(.DASimulations())
##' Initialization function for `DASimulations`
##'
##' @param trialduration see \code{\linkS4class{DASimulations}}
##' @param \dots additional parameters from \code{\link{Simulations}}
##' @return the \code{\linkS4class{DASimulations}} object
##'
##' @export
##' @keywords methods
DASimulations <- function(trialduration,
...)
{
start <- Simulations(...)
.DASimulations(start,
trialduration=trialduration)
}
## ---------------------------------------------------------------------------------------------
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Defines functions DASimulations PseudoDualFlexiSimulations PseudoDualSimulations PseudoSimulations DualSimulations Simulations GeneralSimulations
Documented in DASimulations DualSimulations GeneralSimulations PseudoDualFlexiSimulations PseudoDualSimulations PseudoSimulations Simulations
#####################################################################################
## Author: Daniel Sabanes Bove [sabanesd *a*t* roche *.* com]
## Wai Yin Yeung [w *.* yeung1 *a*t* lancaster *.* ac *.* uk]
## Project: Object-oriented implementation of CRM designs
##
## Time-stamp: <[Simulations-class.R] by DSB Sam 17/01/2015 19:42>
##
## Description:
## Encapsulate the simulations output in a formal class.
##
## History:
## 12/02/2014 file creation
## 10/07/2015 added Pseudo simulation class
###################################################################################
##' @include helpers.R
##' @include Data-class.R
{}
##' General class for the simulations output
##'
##' This class captures trial simulations.
##'
##' Here also the random generator state before starting the simulation is
##' saved, in order to be able to reproduce the outcome. For this just use
##' \code{\link{set.seed}} with the \code{seed} as argument before running
##' \code{\link{simulate,Design-method}}.
##'
##' @slot data list of produced \code{\linkS4class{Data}} objects
##' @slot doses the vector of final dose recommendations
##' @slot seed random generator state before starting the simulation
##'
##' @export
##' @keywords classes
.GeneralSimulations <-
setClass(Class="GeneralSimulations",
representation(data="list",
doses="numeric",
seed="integer"),
prototype(data=
list(Data(x=1:2,
y=0:1,
doseGrid=1:2),
Data(x=3:4,
y=0:1,
doseGrid=3:4)),
doses=c(1, 2),
seed=1L),
validity=
function(object){
o <- Validate()
nSims <- length(object@data)
o$check(all(sapply(object@data, is, "Data")),
"all data elements must be Data objects")
o$check(identical(length(object@doses), nSims),
"doses must have same length as the data list")
o$result()
})
validObject(.GeneralSimulations())
##' Initialization function for "GeneralSimulations"
##'
##' @param data see \code{\linkS4class{GeneralSimulations}}
##' @param doses see \code{\linkS4class{GeneralSimulations}}
##' @param seed see \code{\linkS4class{GeneralSimulations}}
##' @return the \code{\linkS4class{GeneralSimulations}} object
##'
##' @export
##' @keywords methods
GeneralSimulations <- function(data,
doses,
seed)
{
.GeneralSimulations(data=data,
doses=doses,
seed=safeInteger(seed))
}
##' Class for the simulations output from model based designs
##'
##' This class captures the trial simulations from model based designs.
##' Additional slots fit and stopReasons compared to the general class
##' \code{\linkS4class{GeneralSimulations}}.
##'
##' @slot fit list with the final fits
##' @slot stopReasons list of stopping reasons for each simulation run
##'
##' @export
##' @keywords classes
.Simulations <-
setClass(Class="Simulations",
representation(fit="list",
stopReasons="list"),
## note: this prototype is put together with the prototype
## for GeneralSimulations
prototype(fit=
list(c(0.1, 0.2),
c(0.1, 0.2)),
stopReasons=
list("A", "A")),
contains="GeneralSimulations",
validity=
function(object){
o <- Validate()
nSims <- length(object@data)
o$check(identical(length(object@fit), nSims),
"fit must have same length as data")
o$check(identical(length(object@stopReasons), nSims),
"stopReasons must have same length as data")
o$result()
})
validObject(.Simulations())
##' Initialization function for the "Simulations" class
##'
##' @param fit see \code{\linkS4class{Simulations}}
##' @param stopReasons see \code{\linkS4class{Simulations}}
##' @param \dots additional parameters from \code{\link{GeneralSimulations}}
##' @return the \code{\linkS4class{Simulations}} object
##' @export
##'
##' @keywords methods
Simulations <- function(fit,
stopReasons,
...)
{
start <- GeneralSimulations(...)
.Simulations(start,
fit=fit,
stopReasons=stopReasons)
}
##' Class for the simulations output from dual-endpoint model based designs
##'
##' This class captures the trial simulations from dual-endpoint model based
##' designs. In comparison to the parent class \code{\linkS4class{Simulations}},
##' it contains additional slots to capture the dose-biomarker fits, and the
##' sigma2W and rho estimates.
##'
##' @slot rhoEst the vector of final posterior median rho estimates
##' @slot sigma2West the vector of final posterior median sigma2W estimates
##' @slot fitBiomarker list with the final dose-biomarker curve fits
##'
##' @export
##' @keywords classes
.DualSimulations <-
setClass(Class="DualSimulations",
representation(rhoEst="numeric",
sigma2West="numeric",
fitBiomarker="list"),
prototype(rhoEst=c(0.2, 0.3),
sigma2West=c(0.2, 0.3),
fitBiomarker=
list(c(0.1, 0.2),
c(0.1, 0.2))),
contains="Simulations",
validity=
function(object){
o <- Validate()
nSims <- length(object@data)
o$check(identical(length(object@fitBiomarker), nSims),
"fitBiomarker list has to have same length as data")
o$check(identical(length(object@rhoEst), nSims),
"rhoEst vector has to have same length as data")
o$check(identical(length(object@sigma2West), nSims),
"sigma2West has to have same length as data")
o$result()
})
validObject(.DualSimulations())
##' Initialization function for "DualSimulations"
##'
##' @param rhoEst see \code{\linkS4class{DualSimulations}}
##' @param sigma2West see \code{\linkS4class{DualSimulations}}
##' @param fitBiomarker see \code{\linkS4class{DualSimulations}}
##' @param \dots additional parameters from \code{\link{Simulations}}
##' @return the \code{\linkS4class{DualSimulations}} object
##'
##' @export
##' @keywords methods
DualSimulations <- function(rhoEst,
sigma2West,
fitBiomarker,
...)
{
start <- Simulations(...)
.DualSimulations(start,
rhoEst=rhoEst,
sigma2West=sigma2West,
fitBiomarker=fitBiomarker)
}
##' Class for the summary of general simulations output
##'
##' Note that objects should not be created by users, therefore no
##' initialization function is provided for this class.
##'
##' @slot target target toxicity interval
##' @slot targetDoseInterval corresponding target dose interval
##' @slot nsim number of simulations
##' @slot propDLTs proportions of DLTs in the trials
##' @slot meanToxRisk mean toxicity risks for the patients
##' @slot doseSelected doses selected as MTD
##' @slot toxAtDosesSelected true toxicity at doses selected
##' @slot propAtTarget Proportion of trials selecting target MTD
##' @slot doseMostSelected dose most often selected as MTD
##' @slot obsToxRateAtDoseMostSelected observed toxicity rate at dose most often
##' selected
##' @slot nObs number of patients overall
##' @slot nAboveTarget number of patients treated above target tox interval
##' @slot doseGrid the dose grid that has been used
##' @slot placebo set to TRUE (default is FALSE) for a design with placebo
##'
##' @export
##' @keywords classes
.GeneralSimulationsSummary <-
setClass(Class="GeneralSimulationsSummary",
representation(target="numeric",
targetDoseInterval="numeric",
nsim="integer",
propDLTs="ANY",
meanToxRisk="numeric",
doseSelected="numeric",
toxAtDosesSelected="numeric",
propAtTarget="numeric",
doseMostSelected="numeric",
obsToxRateAtDoseMostSelected="numeric",
nObs="ANY",
nAboveTarget="integer",
doseGrid="numeric",
placebo="logical"))
##' Class for the summary of model-based simulations output
##'
##' In addition to the slots in the parent class
##' \code{\linkS4class{GeneralSimulationsSummary}}, it contains two slots with
##' model fit information.
##'
##' Note that objects should not be created by users, therefore no
##' initialization function is provided for this class.
##'
##' @slot fitAtDoseMostSelected fitted toxicity rate at dose most often selected
##' @slot meanFit list with the average, lower (2.5%) and upper (97.5%)
##' quantiles of the mean fitted toxicity at each dose level
##'
##' @export
##' @keywords classes
.SimulationsSummary <-
setClass(Class="SimulationsSummary",
representation(fitAtDoseMostSelected="numeric",
meanFit="list"),
contains="GeneralSimulationsSummary")
##' Class for the summary of dual-endpoint simulations output
##'
##' In addition to the slots in the parent class
##' \code{\linkS4class{SimulationsSummary}}, it contains two slots for the
##' biomarker model fit information.
##'
##' Note that objects should not be created by users, therefore no
##' initialization function is provided for this class.
##'
##' @slot biomarkerFitAtDoseMostSelected fitted biomarker level at dose most often selected
##' @slot meanBiomarkerFit list with the average, lower (2.5%) and upper (97.5%)
##' quantiles of the mean fitted biomarker level at each dose level
##'
##' @export
##' @keywords classes
.DualSimulationsSummary <-
setClass(Class="DualSimulationsSummary",
contains="SimulationsSummary",
representation=
representation(biomarkerFitAtDoseMostSelected="numeric",
meanBiomarkerFit="list"))
## ==============================================================================
## -------------------------------------------------------------------------------
## class for simulation using pseudo models
## ------------------------------------------------------------------------
##' Class `PseudoSimulations`
##'
##' This is a class which captures the trial simulations from designs using
##' pseudo model. The design for DLE only responses and model from \code{\linkS4class{ModelTox}}
##' class object. It contains all slots from \code{\linkS4class{GeneralSimulations}} object.
##' Additional slots fit and stopReasons compared to the general class
##' \code{\linkS4class{GeneralSimulations}}.
##'
##' @slot fit list of the final values. If samples are involved, these are the final fitted values.
##' If no samples are involved, these are included the final modal estimates of the model parameters
##' and the posterior estimates of the probabilities of the occurrence of a DLE.
##' @slot FinalTDtargetDuringTrialEstimates the vector of all final estimates (the last estimate of) the TDtargetDuringTrial at the end
##' of each simulations/when each trial stops
##' @slot FinalTDtargetEndOfTrialEstimates vector of all final estimates or the last estimate of the TDtargetEndOfTrial when each trial
##' stops
##' @slot FinalTDtargetDuringTrialAtDoseGrid vector of the dose levels at dose grid closest below the final TDtargetDuringTrial estimates
##' @slot FinalTDtargetEndOfTrialAtDoseGrid vector of the dose levels at dose grid closest below the final TDtargetEndOfTrial estimates
##' @slot FinalTDEOTCIs is the list of all 95% credibility interval of the final estimates of the TDtargetEndOfTrial
##' @slot FinalTDEOTRatios is the vector of the ratios of the CI, the ratio of the upper to the lower 95% credibility intervals
##' of the final estimates of the TDtargetEndOfTrial
##' @slot FinalCIs list of all the final 95% credibility intervals of the TDtargetEndofTrial estimates or of the final optimal dose
##' estimates when DLE and efficacy responses are incorporated after each simulations
##' @slot FinalRatios vector of all the final ratios, the ratios of the upper to the lower 95% credibility interval of the
##' final estimates of the TDtargetEndOfTrial or of the final optimal dose estimates (when DLE and efficacy responses are
##' incorporated) after each simulations
##' @slot stopReasons add slot description
##'
##' @export
.PseudoSimulations <-
setClass(Class="PseudoSimulations",
representation(fit="list",
FinalTDtargetDuringTrialEstimates="numeric",
FinalTDtargetEndOfTrialEstimates = "numeric",
FinalTDtargetDuringTrialAtDoseGrid="numeric",
FinalTDtargetEndOfTrialAtDoseGrid ="numeric",
FinalTDEOTCIs="list",
FinalTDEOTRatios="numeric",
FinalCIs="list",
FinalRatios="numeric",
stopReasons="list"),
## note: this prototype is put together with the prototype
## for GeneralSimulations
prototype(FinalTDtargetDuringTrialEstimates= c(0.1,0.1),
FinalTDtargetEndOfTrialEstimates=c(0.1,0.1),
FinalTDtargetDuringTrialAtDoseGrid=c(0.1,0.1),
FinalTDtargetEndOfTrialAtDoseGrid=c(0.1,0.1),
FinalTDEOTCIs=list(c(0.1, 0.2),c(0.1, 0.2)),
FinalTDEOTRatios=c(0.1,0.1),
FinalCIs=list(c(0.1, 0.2),c(0.1, 0.2)),
FinalRatios=c(0.1,0.1),
stopReasons=
list("A", "A")),
contains="GeneralSimulations",
validity=
function(object){
o <- Validate()
nSims <- length(object@data)
o$check(identical(length(object@stopReasons), nSims),
"stopReasons must have same length as data")
o$result()
})
validObject(.PseudoSimulations())
##' Initialization function of the 'PseudoSimulations' class
##' @param fit please refer to \code{\linkS4class{PseudoSimulations}} class object
##' @param FinalTDtargetDuringTrialEstimates please refer to \code{\linkS4class{PseudoSimulations}} class object
##' @param FinalTDtargetEndOfTrialEstimates please refer to \code{\linkS4class{PseudoSimulations}} class object
##' @param FinalTDtargetDuringTrialAtDoseGrid please refer to \code{\linkS4class{PseudoSimulations}} class object
##' @param FinalTDtargetEndOfTrialAtDoseGrid please refer to \code{\linkS4class{PseudoSimulations}} class object
##' @param FinalTDEOTCIs please refer to \code{\linkS4class{PseudoSimulations}} class object
##' @param FinalTDEOTRatios please refer to \code{\linkS4class{PseudoSimulations}} class object
##' @param FinalCIs please refer to \code{\linkS4class{PseudoSimulations}} class object
##' @param FinalRatios please refer to \code{\linkS4class{PseudoSimulations}} class object
##' @param stopReasons please refer to \code{\linkS4class{PseudoSimulations}} class object
##' @param \dots additional parameters from \code{\linkS4class{GeneralSimulations}}
##' @return the \code{\linkS4class{PseudoSimulations}} object
##'
##' @export
PseudoSimulations <- function(fit,
FinalTDtargetDuringTrialEstimates,
FinalTDtargetEndOfTrialEstimates,
FinalTDtargetDuringTrialAtDoseGrid,
FinalTDtargetEndOfTrialAtDoseGrid,
FinalTDEOTCIs,
FinalTDEOTRatios,
FinalCIs,
FinalRatios,
stopReasons,
...)
{
start <- GeneralSimulations(...)
.PseudoSimulations(start,
fit=fit,
FinalTDtargetDuringTrialEstimates=FinalTDtargetDuringTrialEstimates,
FinalTDtargetEndOfTrialEstimates=FinalTDtargetEndOfTrialEstimates,
FinalTDtargetDuringTrialAtDoseGrid=FinalTDtargetDuringTrialAtDoseGrid,
FinalTDtargetEndOfTrialAtDoseGrid= FinalTDtargetEndOfTrialAtDoseGrid,
FinalTDEOTCIs=FinalTDEOTCIs,
FinalTDEOTRatios=FinalTDEOTRatios,
FinalCIs=FinalCIs,
FinalRatios=FinalRatios,
stopReasons=stopReasons)
}
## ===============================================================================
## -------------------------------------------------------------------------------
## Class for Pseudo simulation using DLE and efficacy responses (Pseudo models except 'EffFlexi' model)
## -----------------------------------------------------------------------------------
##' Class `PseudoDualSimulations`
##'
##' This is a class which captures the trial simulations design using both the
##' DLE and efficacy responses. The design of model from \code{\linkS4class{ModelTox}}
##' class and the efficacy model from \code{\linkS4class{ModelEff}} class
##' (except \code{\linkS4class{EffFlexi}} class). It contains all slots from
##' \code{\linkS4class{GeneralSimulations}} and \code{\linkS4class{PseudoSimulations}} object.
##' In comparison to the parent class \code{\linkS4class{PseudoSimulations}},
##' it contains additional slots to
##' capture the dose-efficacy curve and the sigma2 estimates.
##'
##' @slot fitEff list of the final values. If DLE and efficacy samples are generated, it contains the
##' final fitted values. If no DLE and efficacy samples are used, it contains the modal estimates of the
##' parameters in the two models and the posterior estimates of the probabilities of the occurrence of a
##' DLE and the expected efficacy responses.
##' @slot FinalGstarEstimates a vector of the final estimates of Gstar at the end of each simulations.
##' @slot FinalGstarAtDoseGrid is a vector of the final estimates of Gstar at dose Grid at the end of each simulations
##' @slot FinalGstarCIs is the list of all 95% credibility interval of the final estimates of Gstar
##' @slot FinalGstarRatios is the vector of the ratios of the CI, the ratio of the upper to the lower 95% credibility interval
##' of the final estimates of Gstar
##' @slot FinalOptimalDose is the vector of the final optimal dose, the minimum of the final TDtargetEndOfTrial estimates and Gstar
##' estimates
##' @slot FinalOptimalDoseAtDoseGrid is the vector of the final optimal dose, the minimum of the final TDtargetEndOfTrial estimates
##' and Gstar estimates at dose Grid
##' @slot sigma2est the vector of the final posterior mean sigma2 estimates
##'
##' @export
.PseudoDualSimulations <-
setClass(Class="PseudoDualSimulations",
representation(fitEff="list",
FinalGstarEstimates="numeric",
FinalGstarAtDoseGrid="numeric",
FinalGstarCIs="list",
FinalGstarRatios="numeric",
FinalOptimalDose="numeric",
FinalOptimalDoseAtDoseGrid="numeric",
sigma2est="numeric"),
prototype( FinalGstarEstimates=c(0.1,0.1),
FinalGstarAtDoseGrid=c(0.1,0.1),
FinalGstarCIs=list(c(0.1, 0.2),
c(0.1, 0.2)),
FinalGstarRatios=c(0.01,0.01),
FinalOptimalDose=c(0.01,0.01),
FinalOptimalDoseAtDoseGrid=c(0.01,0.01),
sigma2est= c(0.001,0.002)),
contains="PseudoSimulations",
validity=
function(object){
o <- Validate()
nSims <- length(object@data)
o$check(identical(length(object@sigma2est),nSims),
"sigma2est has to have same length as data")
o$result()
})
validObject(.PseudoDualSimulations())
##' Initialization function for 'DualPseudoSimulations' class
##' @param fitEff please refer to \code{\linkS4class{PseudoDualSimulations}} class object
##' @param FinalGstarEstimates please refer to \code{\linkS4class{PseudoDualSimulations}} class object
##' @param FinalGstarAtDoseGrid please refer to \code{\linkS4class{PseudoDualSimulations}} class object
##' @param FinalGstarCIs please refer to \code{\linkS4class{PseudoDualSimulations}} class object
##' @param FinalGstarRatios please refer to \code{\linkS4class{PseudoDualSimulations}} class object
##' @param FinalOptimalDose please refer to \code{\linkS4class{PseudoDualSimulations}} class object
##' @param FinalOptimalDoseAtDoseGrid please refer to \code{\linkS4class{PseudoDualSimulations}} class object
##' @param sigma2est please refer to \code{\linkS4class{PseudoDualSimulations}} class object
##' @param \dots additional parameters from \code{\linkS4class{PseudoSimulations}}
##' @return the \code{\linkS4class{PseudoDualSimulations}} object
PseudoDualSimulations <- function(fitEff,
FinalGstarEstimates,
FinalGstarAtDoseGrid,
FinalGstarCIs,
FinalGstarRatios,
FinalOptimalDose,
FinalOptimalDoseAtDoseGrid,
sigma2est,
...)
{
start <- PseudoSimulations(...)
.PseudoDualSimulations(start,
fitEff=fitEff,
FinalGstarEstimates=FinalGstarEstimates,
FinalGstarAtDoseGrid=FinalGstarAtDoseGrid,
FinalGstarCIs=FinalGstarCIs,
FinalGstarRatios=FinalGstarRatios,
FinalOptimalDose=FinalOptimalDose,
FinalOptimalDoseAtDoseGrid=FinalOptimalDoseAtDoseGrid,
sigma2est=sigma2est)
}
## -------------------------------------------------------------------------------
## Class for Pseudo simulation using DLE and efficacy responses using 'EffFlex' efficacy model
## -----------------------------------------------------------------------------------
##' This is a class which captures the trial simulations design using both the
##' DLE and efficacy responses. The design of model from \code{\linkS4class{ModelTox}}
##' class and the efficacy model from \code{\linkS4class{EffFlexi}} class
##' It contains all slots from
##' \code{\linkS4class{GeneralSimulations}}, \code{\linkS4class{PseudoSimulations}}
##' and \code{\linkS4class{PseudoDualSimulations}} object.
##' In comparison to the parent class \code{\linkS4class{PseudoDualSimulations}},
##' it contains additional slots to
##' capture the sigma2betaW estimates.
##'
##' @slot sigma2betaWest the vector of the final posterior mean sigma2betaW estimates
##'
##' @export
##' @keywords class
.PseudoDualFlexiSimulations <-
setClass(Class="PseudoDualFlexiSimulations",
representation(sigma2betaWest="numeric"),
prototype(sigma2betaWest= c(0.001,0.002)),
contains="PseudoDualSimulations",
validity=
function(object){
o <- Validate()
nSims <- length(object@data)
o$check(identical(length(object@sigma2betaWest),nSims),
"sigma2betaWest has to have same length as data")
o$result()
})
validObject(.PseudoDualFlexiSimulations())
##' Initialization function for 'PseudoDualFlexiSimulations' class
##' @param sigma2betaWest please refer to \code{\linkS4class{PseudoDualFlexiSimulations}} class object
##' @param \dots additional parameters from \code{\linkS4class{PseudoDualSimulations}}
##' @return the \code{\linkS4class{PseudoDualFlexiSimulations}} object
PseudoDualFlexiSimulations <- function(sigma2betaWest,
...)
{
start <- PseudoDualSimulations(...)
.PseudoDualFlexiSimulations(start,
sigma2betaWest=sigma2betaWest)
}
## -------------------------------------------------------------------------------------------------------
## ================================================================================================
##' Class for the summary of pseudo-models simulations output
##'
##' Note that objects should not be created by users, therefore no
##' initialization function is provided for this class.
##'
##' @slot targetEndOfTrial the target probability of DLE wanted at the end of a trial
##' @slot targetDoseEndOfTrial the dose level corresponds to the target probability
##' of DLE wanted at the end of a trial, TDEOT
##' @slot targetDoseEndOfTrialAtDoseGrid the dose level at dose grid corresponds to the target probability
##' of DLE wanted at the end of a trial
##' @slot targetDuringTrial the target probability of DLE wanted during a trial
##' @slot targetDoseDuringTrial the dose level corresponds to the target probability of DLE
##' wanted during the trial. TDDT
##' @slot targetDoseDuringTrialAtDoseGrid the dose level at dose grid corresponds to the target probability
##' of DLE wanted during a trial
##' @slot TDEOTSummary the six-number table summary, include the lowest, the 25th precentile (lower quartile),
##' the 50th percentile (median), the mean, the 27th percentile and the highest values of the
##' final dose levels obtained corresponds to the target probability of DLE
##' want at the end of a trial across all simulations
##' @slot TDDTSummary the six-number table summary, include the lowest, the 25th precentile (lower quartile),
##' the 50th percentile (median), the mean, the 27th percentile and the highest values of the
##' final dose levels obtained corresponds to the target probability of DLE
##' want during a trial across all simulations
##' @slot FinalDoseRecSummary the six-number table summary, include the lowest, the 25th precentile (lower quartile),
##' the 50th percentile (median), the mean, the 27th percentile and the highest values of the
##' final optimal doses, which is either the TDEOT when only DLE response are incorporated into
##' the escalation procedure or the minimum of the TDEOT and Gstar when DLE and efficacy responses are
##' incorporated, across all simulations
##' @slot ratioTDEOTSummary the six-number summary table of the final ratios of the upper to the lower 95%
##' credibility intervals of the final TDEOTs across all simulations
##' @slot FinalRatioSummary the six-number summary table of the final ratios of the upper to the lower 95%
##' credibility intervals of the final optimal doses across all simulations
##' #@slot doseRec the dose level that will be recommend for subsequent study
##' @slot nsim number of simulations
##' @slot propDLE proportions of DLE in the trials
##' @slot meanToxRisk mean toxicity risks for the patients
##' @slot doseSelected doses selected as MTD (targetDoseEndOfTrial)
##' @slot toxAtDosesSelected true toxicity at doses selected
##' @slot propAtTargetEndOfTrial Proportion of trials selecting at the doseGrid closest below the MTD, the
##' targetDoseEndOfTrial
##' @slot propAtTargetDuringTrial Proportion of trials selecting at the doseGrid closest below the
##' targetDoseDuringTrial
##' @slot doseMostSelected dose most often selected as MTD
##' @slot obsToxRateAtDoseMostSelected observed toxicity rate at dose most often
##' selected
##' @slot nObs number of patients overall
##' @slot nAboveTargetEndOfTrial number of patients treated above targetDoseEndOfTrial
##' @slot nAboveTargetDuringTrial number of patients treated above targetDoseDuringTrial
##' @slot doseGrid the dose grid that has been used
##' @slot fitAtDoseMostSelected fitted toxicity rate at dose most often selected
##' @slot meanFit list with the average, lower (2.5%) and upper (97.5%)
##' quantiles of the mean fitted toxicity at each dose level
##'
##'
##' @export
##' @keywords classes
.PseudoSimulationsSummary <-
setClass(Class="PseudoSimulationsSummary",
representation(targetEndOfTrial="numeric",
targetDoseEndOfTrial="numeric",
targetDoseEndOfTrialAtDoseGrid="numeric",
targetDuringTrial="numeric",
targetDoseDuringTrial="numeric",
targetDoseDuringTrialAtDoseGrid="numeric",
TDEOTSummary="table",
TDDTSummary="table",
FinalDoseRecSummary="table",
ratioTDEOTSummary="table",
FinalRatioSummary="table",
#doseRec="numeric",
nsim="integer",
propDLE="numeric",
meanToxRisk="numeric",
doseSelected="numeric",
toxAtDosesSelected="numeric",
propAtTargetEndOfTrial="numeric",
propAtTargetDuringTrial="numeric",
doseMostSelected="numeric",
obsToxRateAtDoseMostSelected="numeric",
nObs="integer",
nAboveTargetEndOfTrial="integer",
nAboveTargetDuringTrial="integer",
doseGrid="numeric",
fitAtDoseMostSelected="numeric",
meanFit="list"))
## ---------------------------------------------------------------------------------------------
##' Class for the summary of the dual responses simulations using pseudo models
##'
##' It contains all slots from \code{\linkS4class{PseudoSimulationsSummary}} object. In addition to
##' the slots in the parent class \code{\linkS4class{PseudoSimulationsSummary}}, it contains four
##' more slots for the efficacy model fit information.
##'
##' Note that objects should not be created by users, therefore no initialization function
##' is provided for this class.
##'
##' @slot targetGstar the target dose level such that its gain value is at maximum
##' @slot targetGstarAtDoseGrid the dose level at dose Grid closest and below Gstar
##' @slot GstarSummary the six-number table summary (lowest, 25th, 50th (median), 75th percentile, mean
##' and highest value) of the final Gstar values obtained across all simulations
##' @slot ratioGstarSummary the six-number summary table of the ratios of the upper to the lower 95%
##' credibility intervals of the final Gstar across all simulations
##' @slot EffFitAtDoseMostSelected fitted expected mean efficacy value at dose most often
##' selected
##' @slot meanEffFit list with mean, lower (2.5%) and upper (97.5%) quantiles of the fitted expected
##' efficacy value at each dose level.
##'
##' @export
##' @keywords class
.PseudoDualSimulationsSummary <-
setClass(Class="PseudoDualSimulationsSummary",
contains="PseudoSimulationsSummary",
representation=
representation(targetGstar="numeric",
targetGstarAtDoseGrid="numeric",
GstarSummary="table",
ratioGstarSummary="table",
EffFitAtDoseMostSelected="numeric",
meanEffFit="list"))
## ---------------------------------------------------------------------------------------------
##' Class for the simulations output from DA based designs
##'
##' This class captures the trial simulations from DA based
##' designs. In comparison to the parent class \code{\linkS4class{Simulations}},
##' it contains additional slots to capture the time to DLT fits, additional
##' parameters and the trial duration.
##'
##' @slot trialduration the vector of trial duration values for all simulations.
##'
##' @export
##' @keywords classes
.DASimulations <-
setClass(Class="DASimulations",
representation(trialduration="numeric"),
prototype(trialduration=rep(0,2)),
contains="Simulations",
validity=
function(object){
o <- Validate()
nSims <- length(object@data)
o$check(identical(length(object@trialduration), nSims),
"trialduration vector has to have same length as data")
o$result()
})
validObject(.DASimulations())
##' Initialization function for `DASimulations`
##'
##' @param trialduration see \code{\linkS4class{DASimulations}}
##' @param \dots additional parameters from \code{\link{Simulations}}
##' @return the \code{\linkS4class{DASimulations}} object
##'
##' @export
##' @keywords methods
DASimulations <- function(trialduration,
...)
{
start <- Simulations(...)
.DASimulations(start,
trialduration=trialduration)
}
## ---------------------------------------------------------------------------------------------
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