slca (version 1.3.0)

simulate.slca: Simulate Data from an slca Model

Description

Simulates data based on a specified slca model. If the model parameters are not already estimated, they can either be provided by the user or generated randomly.

Usage

# S3 method for slca
simulate(object, nsim = 500, seed = NULL, parm, nlevel, ...)

Value

A list with the following components:

class

A data.frame containing the assigned latent class for each individual across all latent class variables.

response

A data.frame containing the simulated manifest item responses.

Arguments

object

an slca object representing the model from which data will be simulated.

nsim

an integer specifying the number of response observations to simulate. The default is 500.

seed

an integer specifying the random seed for reproducibility. If not provided, results will vary across runs.

parm

a user-specified set of parameters to guide the simulation. This is required if the model has not been previously estimated.

nlevel

an integer or integer vector specifying the number of levels for each manifest item in the model. If a single integer is provided, all manifest items will have the same number of levels. The default is 2.

...

Additional arguments passed to other methods.

Examples

m1 <- slca(lc1[3] ~ x1 + x2 + x3 + x4 + x5,
              lc2[4] ~ y1 + y2 + y3 + y4 + y5)
sim <- simulate(m1, 1000)
sapply(sim$class, table)

# simulate data with defined number of levels of manifest items
m2 <- slca(lc1[3] ~ x1 + x2 + x3 + x4)
sim <- simulate(m2, nlevel = c(3, 3, 3, 3))
d <- sim$response
sapply(d, table)

sim <- simulate(m2, nlevel = c(x1 = 2, x3 = 3, x4 = 4, x5 = 5))
d <- sim$response
sapply(d, table)

# simulate data with user-defined parameters
pi <- rep(1 / 3, 3)
rho <- c(.9, .1, .9, .1, .9, .1, .9, .1,
         .9, .1, .9, .1, .1, .9, .1, .9,
         .1, .9, .1, .9, .1, .9, .1, .9)
par <- c(pi, rho)
m3 <- slca(lc[3] ~ y1 + y2 + y3 + y4)
sim <- simulate(m3, parm = par)
mf <- estimate(m3, sim$response)
param(mf)