Description of the R functions associated to covariate models

addCategoricalTransformedCovariate Create a new categorical covariate by transforming an existing one.
addContinuousTransformedCovariate Create a new continuous covariate by transforming an existing one.
addMixture .
getCovariateInformation Get the name, the type and the values of the covariates present in the project.
removeCovariate Remove some of the transformed covariates (discrete and continuous) and/or latent covariates.

Add categorical transformed covariate

Description

Create a new categorical covariate by transforming an existing one. Transformed covariates cannot be use to produce new covariates.
Call getCovariateInformation to know which covariates can be transformed.

Usage

addCategoricalTransformedCovariate(...)

Arguments

…
A list of comma-separated pairs {transformedCovariateName = { from = (array<(string)>)[“basicCovariateNames”], transformed = (array<array<string>>)”transformation”} }

See Also

getCovariateInformation removeCovariate

Click here to see examples

## Not run:

addCategoricalTransformedCovariate( Country2 = list( reference = “A1”, from = “Country”,

transformed = list( A1 = c(“A”,”B”), A2 = c(“C”) ) ) )

## End(Not run)

)
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Add continuous transformed covariate

Description

Create a new continuous covariate by transforming an existing one. Transformed covariates cannot be use to produce new covariates.
Call getCovariateInformation to know which covariates can be transformed.

Usage

addContinuousTransformedCovariate(...)

Arguments

…
A list of comma-separated pairs {transformedCovariateName = (string)”transformation”}

See Also

getCovariateInformation removeCovariate

Click here to see examples

## Not run:

addContinuousTransformedCovariate( tWt2 = “3*exp(Wt)” )

## End(Not run)

)
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Add mixture to the covariate model
Add a new latent covariate to the current model giving its name and its modality number.

Description

Add mixture to the covariate model

Add a new latent covariate to the current model giving its name and its modality number.

Usage

addMixture(...)

Arguments

…
A list of comma-separated pairs {latentCovariateName = (int)modalityNumber}

See Also

getCovariateInformation removeCovariate

Click here to see examples

## Not run:

addMixture(lcat = 2)

## End(Not run)

)
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Get covariates information

Description

Get the name, the type and the values of the covariates present in the project.

Usage

getCovariateInformation()

Value

A list containing the following fields :

  • name : (vector<string>) covariate names
  • type : (vector<string>) covariate types. Existing types are “continuous”, “continuoustransformed”, “categorical”, “categoricaltransformed” and “latent”.
  • modalityNumber : (vector<int>) number of modalities (for latent covariates only)
  • covariate : a data frame giving the values of continuous and categorical covariates for each subject.
    Latent covariate values exist only if they have been estimated, ie if the covariate is used and if the population parameters have been estimated.
    Call getEstimatedIndividualParameters to retrieve them.

Click here to see examples

## Not run:

info = getCovariateInformation()

info

-> $name

c(“sex”,”wt”,”lcat”)

-> $type

c(sex = “categorical”, wt = “continuous”, lcat = “latent”)

-> $modalityNumber

c(lcat = 2)

-> $covariate

id sex wt

1 M 66.7

. . .

N F 59.0

## End(Not run)

)
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Remove covariate

Description

Remove some of the transformed covariates (discrete and continuous) and/or latent covariates.
Call getCovariateInformation to know which covariates can be removed.

Usage

removeCovariate(...)

Arguments

…
A list of covariate names.

See Also

getCovariateInformation addContinuousTransformedCovariate addCategoricalTransformedCovariate
addMixture

Click here to see examples

## Not run:

removeCovariate(“tWt”,”lcat1″)

## End(Not run)

)
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