sim_subject_attributes {simcdm} | R Documentation |
Generate a sample from the \mathbf{α}_c = (α_{c1}, …, α_{cK})' attribute profile matrix for members of class c such that α_{ck} ' is 1 if members of class c possess skill k and zero otherwise.
sim_subject_attributes(N, K, probs = NULL)
N |
Number of Observations |
K |
Number of Skills |
probs |
A |
A N by K matrix
of latent classes
corresponding to entry c of pi based upon
mastery and nonmastery of the K skills.
James Joseph Balamuta and Steven Andrew Culpepper
simcdm::attribute_classes()
and simcdm::attribute_inv_bijection()
# 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)