Description of the R functions associated to the individual parameter models

getIndividualParameterModel Get a summary of the information concerning the individual parameter model.
getVariabilityLevels Get a summary of the variability levels (inter-individual and/or intra-individual variability) present in the current project.
setCorrelationBlocks Define the correlation block structure associated to some of the variability levels of the current project.
setCovariateModel Set which are the covariates influencing individual parameters present in the project.
setIndividualParameterDistribution Set the distribution of the estimated parameters.
setIndividualParameterVariability Add or remove inter-individual and/or intra-individual variability from some of the individual parameters present in the project.
setIndividualLogitLimits Set the limits for logit distributions.

Get individual parameter model

Description

Get a summary of the information concerning the individual parameter model. The available information are:

  • name: (string) name of the individual parameter
  • distribution: (string) distribution of the parameter values. The distribution type can be “normal”, “logNormal”, or “logitNormal”.
  • formula: (string) formula applied on individual parameters distribution
  • variability: a list giving, for each variability level, if individual parameters have variability or not
  • covariateModel: a list giving, for each individual parameter, if the related covariates are used or not.
    If no covariate is used, this field is empty.
  • correlationBlocks : a list giving, for each variability level, the blocks of the correlation matrix of the random effects.
    A block is represented by a vector of individual parameter names. If there is no block, this field is empty.

Usage

getIndividualParameterModel()

Value

A list of individual parameter model properties.

See Also

setIndividualParameterDistribution setIndividualParameterVariability setCovariateModel

Click here to see examples

## Not run:

indivModel = getIndividualParameterModel()

indivModel

-> $name

c(“ka”,”V”,”Cl”)

$distribution

c(ka = “logNormal”, V = “normal”, Cl = “logNormal”)

$formula

“\\tlog(ka) = log(ka_pop) + eta_ka\\n\\n\\tlV = V_pop + eta_V\\n\\n\\tlog(Cl) = log(Cl_pop) + eta_Cl\\n\\n”

$variability

list( id = c(ka = TRUE, V = FALSE, Cl = TRUE) )

$covariateModel

list( ka = c(age = TRUE, sex = FALSE, wt = TRUE),

V = c(age = FALSE, sex = FALSE, wt = FALSE),

Cl = c(age = FALSE, sex = FALSE, wt = FALSE) )

$correlationBlocks

list( id = c(“ka”,”V”,”Tlag”) )

## End(Not run)

)
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Get variability levels

Description

Get a summary of the variability levels (inter-individual and/or intra-individual variability) present in the current project.

Usage

getVariabilityLevels()

Value

A collection of the variability levels present in the currently loaded project.

Click here to see examples

## Not run:

getVariabilityLevels()

## End(Not run)

)
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Set correlation block structure

Description

Define the correlation block structure associated to some of the variability levels of the current project.
Call getVariabilityLevels to get a list of the variability levels and getIndividualParameterModel to get a list of the available individual parameters within the current project.

Usage

setCorrelationBlocks(...)

Arguments


A list of comma-separated pairs {variabilityLevel = vector< (array<string>)parameterNames} > }.

See Also

getVariabilityLevels getIndividualParameterModel

Click here to see examples

## Not run:

setCorrelationBlocks(id = list( c(“ka”,”V”,”Tlag”) ), iov1 = list( c(“ka”,”Cl”), c(“Tlag”,”V”) ) )

## End(Not run)

)
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Set covariate model

Description

Set which are the covariates influencing individual parameters present in the project.
Call getIndividualParameterModel to get a list of the individual parameters present within the current project.
and getCovariateInformation to know which are the available covariates for a given level of variability and a given individual parameter.

Usage

setCovariateModel(...)

Arguments


A list of comma-separated pairs {parameterName = { covariateName = (bool)isInfluent, …} }

See Also

getCovariateInformation

Click here to see examples

## Not run:

setCovariateModel( ka = c( Wt = FALSE, tWt = TRUE, lcat2 = TRUE),

Cl = c( SEX = TRUE )

)

## End(Not run)

)
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Set individual parameter distribution

Description

Set the distribution of the estimated parameters.
Available distributions are “normal”, “logNormal” and “logitNormal”.
Call getIndividualParameterModel to get a list of the available individual parameters within the current project.

Usage

setIndividualParameterDistribution(...)

Arguments


A list of comma-separated pairs {parameterName = (string)”distribution”}.

See Also

getIndividualParameterModel

Click here to see examples

## Not run:

setIndividualParameterDistribution(V = “logNormal”)

setIndividualParameterDistribution(Cl = “normal”, V = “logNormal”)

## End(Not run)

)
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Individual variability management

Description

Add or remove inter-individual and/or intra-individual variability from some of the individual parameters present in the project.
Call getIndividualParameterModel to get a list of the available parameters within the current project.

Usage

setIndividualParameterVariability(...)

Arguments


A list of comma-separated pairs {variabilityLevel = {individualParameterName = (bool)hasVariability} }.

See Also

getIndividualParameterModel

Click here to see examples

## Not run:

setIndividualParameterVariability(ka = TRUE, V = FALSE)

setIndividualParameterVariability(id = list(ka = TRUE), iov1 = list(ka = FALSE))

## End(Not run)

)
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Set limits for logit distributions

Description

Set the minimum and the maximum values between the individual parameter can be used. Used only if the distribution of the parameter is “logitNormal”, else wise it will not be taken into account.

Usage

setIndividualLogitLimits(...)

Arguments


A list of comma-separated pairs {individualParameter = [(double)min,(double)max] }

See Also

getIndividualParameterModel

Click here to see examples

##Not run:

setIndividualLogitLimits( V = c(0, 1), ka = c(-1, 2) )

##End(Not run)

)
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