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# [COVARIATE]

### Description

The section [COVARIATE] defines the probability distribution of the covariates.

### Scope

The [COVARIATE] section is used in Mlxtran models for simulation with Mlxplore or Simulx. It is only needed for models that have parameters that depend on covariates. Mlxtran models for Monolix do not need this section because the covariate model is defined via the user interface.

### Inputs

Inputs to the [COVARIATE] section are provided through the list input = { }. The inputs are typically the list of parameters that are required for defining the covariate distributions (mean, standard deviation, . . . ). The parameters in the input list are provided through Mlxplore or through the calling R-script in the case of Simulx.

[COVARIATE]
input = {weight_pop, omega_weight}

### Outputs

Every variable that has been defined in the [COVARIATE] section can be an output. Outputs from the [COVARIATE] section can be an input for the [INDIVIDUAL] section but not the [LONGITUDINAL] section. [COVARIATE] output to [INDIVIDUAL] input matching is made by matching any parameter names in the [COVARIATE] section with parameters in the inputs = { } list of the [INDIVIDUAL] section.

### Usage

All distributions that can be used to define the covariate distribution are listed in link.

A typical [COVARIATE] section has the following syntax. Here a covariate c is defined such that c = 0 if z <= -0.2533 and c = 1 otherwise, where $z ~ N(0, 1)$. The inputs of the covariate section are weight_pop, omega_weight and the output is $cz$.

[COVARIATE]
input = {weight_pop, omega_weight}
DEFINITION:
z = {distribution=normal, mean=weight_pop, sd=omega_weight}
EQUATION:
if z<= -0.2533 ; P(z<=-0.2533)=0.4
cz = 0
else
cz = 1
end
c=cz