| 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
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
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
Click here to see examples
##Not run:
setIndividualLogitLimits( V = c(0, 1), ka = c(-1, 2) )
##End(Not run)
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