Extract exogenous variables (predictors), endogenous variables (outcomes), latent variables (random effects), manifest (observed) variables from a lvm object.

vars(x,...)

endogenous(x,...)

exogenous(x,...)

manifest(x,...)

latent(x,...)

# S3 method for lvm
exogenous(x, xfree = TRUE,...) <- value

# S3 method for lvm
exogenous(x,variable,latent=FALSE,index=TRUE,...)

# S3 method for lvm
latent(x,clear=FALSE,...) <- value

## Arguments

x lvm-object Additional arguments to be passed to the low level functions list of variables to alter Logical defining whether latent variables without parents should be included in the result For internal use only Logical indicating whether to add or remove latent variable status For internal use only Formula or character vector of variable names.

## Value

Vector of variable names.

## Details

vars returns all variables of the lvm-object including manifest and latent variables. Similarily manifest and latent returns the observered resp. latent variables of the model. exogenous returns all manifest variables without parents, e.g. covariates in the model, however the argument latent=TRUE can be used to also include latent variables without parents in the result. Pr. default lava will not include the parameters of the exogenous variables in the optimisation routine during estimation (likelihood of the remaining observered variables conditional on the covariates), however this behaviour can be altered via the assignment function exogenous<- telling lava which subset of (valid) variables to condition on. Finally latent returns a vector with the names of the latent variables in x. The assigment function latent<- can be used to change the latent status of variables in the model.

endogenous, manifest, latent, exogenous, vars

Klaus K. Holst

## Examples


g <- lvm(eta1 ~ x1+x2)
regression(g) <- c(y1,y2,y3) ~ eta1
latent(g) <- ~eta1
endogenous(g)
#> [1] "y1" "y2" "y3"exogenous(g)
#> [1] "x1" "x2"identical(latent(g), setdiff(vars(g),manifest(g)))
#> [1] TRUE