extractData: Extract Data From a Latent Variable Model

In lavaSearch2: Tools for Model Specification in the Latent Variable Framework

Extract Data From a Latent Variable Model

Description

Extract data from a latent variable model.

Usage

extractData(object, design.matrix, as.data.frame, envir, rm.na)

## S3 method for class 'lvmfit'
extractData(
  object,
  design.matrix = FALSE,
  as.data.frame = TRUE,
  envir = environment(),
  rm.na = TRUE
)

Arguments

object	the fitted model.
design.matrix	[logical] should the data be extracted after transformation (e.g. conversion of categorical variables to dummy variables)? Otherwise the original data will be returned.
as.data.frame	[logical] should the output be converted into a data.frame object?
envir	[environment] the environment from which to search the data.
rm.na	[logical] should the lines containing missing values in the dataset be removed?

Value

a dataset.

Examples

#### simulate data ####
set.seed(10)
n <- 101

Y1 <- rnorm(n, mean = 0)
Y2 <- rnorm(n, mean = 0.3)
Id <- findInterval(runif(n), seq(0.1,1,0.1))
data.df <- rbind(data.frame(Y=Y1,G="1",Id = Id),
           data.frame(Y=Y2,G="2",Id = Id)       
           )

#### latent variable model ####
library(lava)
e.lvm <- estimate(lvm(Y ~ G), data = data.df)
extractData(e.lvm)
extractData(e.lvm, design.matrix = TRUE)

lavaSearch2 documentation built on April 12, 2023, 12:33 p.m.