sdirt: Simulated Data for a Signal Detection IRT Model
In mlthom/CogIRT: Cognitive Testing Using Item Response Theory

sdirt

R Documentation

Simulated Data for a Signal Detection IRT Model

Data and parameters were simulated based on the example provided in the sim_dich_response.R function. This dataset is for a sample size of 50.

sdirt

A list with the following elements:

y: Matrix of dichotomous responses.
ystar: Matrix of latent response variates.
nu: Mean of the item intercept parameters (scalar).
lambda: Matrix of item structure parameters.
gamma: Matrix of experimental structure parameters.
omega: Subject-level effects of the experimental manipulation.
zeta: Condition-level prediction errors.
omega_mu: Vector of means for the subject-level effects of the experimental manipulation (1 by K * M).
omega_sigma2: Covariance matrix for the subject-level effects of the experimental manipulation (K * M by K * M).
zeta_mu: Vector of means for the condition-level prediction errors (1 by J * M).
zeta_sigma2: Covariance matrix for the condition-level prediction errors (J * M by J * M).