sim_slcm: Simulate Ordinal Item Data from a Sparse Latent Class Model

In ohoegdm: Ordinal Higher-Order Exploratory General Diagnostic Model for Polytomous Data

Simulate Ordinal Item Data from a Sparse Latent Class Model

Description

Simulate Ordinal Item Data from a Sparse Latent Class Model

Usage

sim_slcm(N, J, M, nClass, CLASS, Atable, BETA, KAPPA)

Arguments

N	Number of Observations
J	Number of Items
M	Number of Item Categories (2, 3, ..., M)
nClass	Number of Latent Classes
CLASS	A vector of N observations containing the class ID of the subject.
Atable	A matrix of dimensions M^K \times M^O containing the attribute classes in bijection-form. Note, O refers to the model's highest interaction order.
BETA	A matrix of dimensions J \times M^K containing the coefficients of the reparameterized β matrix.
KAPPA	A matrix of dimensions J \times M containing the category threshold parameters

Value

An ordinal item matrix of dimensions N x J with M response levels.

See Also

ohoegdm

ohoegdm documentation built on March 18, 2022, 6:01 p.m.