TwoPLChoicemcmc {cIRT}

Two Parameter Choice IRT Model MCMC

Description

Performs an MCMC routine for a two parameter IRT Model using Choice Data

Usage

TwoPLChoicemcmc(
  unique_subject_ids,
  subject_ids,
  choices_nk,
  fixed_effects,
  B,
  rv_effects_design,
  gamma,
  beta,
  zeta_rv,
  Sigma_zeta_inv,
  Y,
  theta0,
  a0,
  b0,
  mu_xi0,
  Sig_xi0
)

Arguments

unique_subject_ids

A vector with length N \times 1 containing unique subject IDs.

subject_ids

A vector with length NK \times 1 containing subject IDs.

choices_nk

A vector with length NK \times 1 containing subject choices.

fixed_effects

A matrix with dimensions NK \times P_1 containing fixed effect design matrix without theta.

B

A V dimensional column vector relating \theta_i and \zeta_i.

rv_effects_design

A matrix with dimensions NK \times V containing random effect variables.

gamma

A vector with dimensions P \times 1 containing fixed parameter estimates, where P = P_1 + P_2

beta

A vector with dimensions P_2 containing random parameter estimates.

zeta_rv

A matrix with dimensions N \times V containing random parameter estimates.

Sigma_zeta_inv

A matrix with dimensions P_2 \times P_2.

Y

A matrix of dimensions N \times J for Dichotomous item responses

theta0

A vector of length N \times 1 for latent theta.

a0

A vector of length J for item discriminations.

b0

A vector of length J for item locations.

mu_xi0

A vector of dimension 2 (i.e. c(0,1)) that is a prior for item parameter means.

Sig_xi0

A matrix of dimension 2x2 (i.e. diag(2)) that is a prior for item parameter vc matrix.

Value

A list that contains:

ai1

A vector of length J

bi1

A vector of length J

theta1

A vector of length N

Z_c

A matrix of length NK

Wzeta_0

A matrix of length NK

Author(s)

Steven Andrew Culpepper and James Joseph Balamuta

See Also

cIRT(), rmvnorm(), and riwishart()

Examples

## Not run: 
# Call with the following data:
TwoPLChoicemcmc(cogDAT, theta0, a0, b0, mu_xi0, Sig_xi0)

## End(Not run)