sim_subject_attributes function

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

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.

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.

Returns

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

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)

See Also

attribute_classes() and attribute_inv_bijection()

Author(s)

James Joseph Balamuta and Steven Andrew Culpepper