sim_subject_attributes: Simulate Subject Latent Attribute Profiles \mathbf{alpha}_c

In simcdm: Simulate Cognitive Diagnostic Model ('CDM') Data

Simulate Subject Latent Attribute Profiles \mathbf{\alpha}_c

Description

Generate a sample from the \mathbf{\alpha}_c = (\alpha_{c1}, \ldots, \alpha_{cK})' attribute profile matrix for members of class c such that \alpha_{ck} ' is 1 if members of class c possess skill k and zero otherwise.

Usage

sim_subject_attributes(N, K, probs = NULL)

Arguments

N	Number of Observations
K	Number of Skills
probs	A vector of probabilities that sum to 1.

Value

A N by K matrix of latent classes corresponding to entry c of pi based upon mastery and nonmastery of the K skills.

Author(s)

James Joseph Balamuta and Steven Andrew Culpepper

See Also

attribute_classes() and attribute_inv_bijection()

Examples

# Define number of subjects and attributes
N = 100
K = 3

# Generate a sample from the Latent Attribute Profile (Alpha) Matrix
# By default, we sample from a uniform distribution weighting of classes.
alphas_builtin = sim_subject_attributes(N, K)

# Generate a sample using custom probabilities from the
# Latent Attribute Profile (Alpha) Matrix
probs = rep(1 / (2 ^ K), 2 ^ K)
alphas_custom = sim_subject_attributes(N, K, probs)

simcdm documentation built on May 29, 2024, 2:09 a.m.