mirtjml_expr {mirtjml}

Constrained joint maximum likelihood estimation for exploratory item factor analysis on the multidimensional two parameter logistic model.

Description

Constrained joint maximum likelihood estimation for exploratory item factor analysis on the multidimensional two parameter logistic model.

Usage

mirtjml_expr(
  response,
  K,
  theta0 = NULL,
  A0 = NULL,
  d0 = NULL,
  cc = NULL,
  tol = 5,
  print_proc = TRUE
)

Arguments

response

N by J matrix containing 0/1/NA responses, where N is the number of respondents, J is the number of items, and NA indicates a missing response.

K

The number of factors in exploratory item factor analysis.

theta0

N by K matrix, the initial value of latent factor scores for each respondent.

A0

J by K matrix, the initial value of loading matrix.

d0

Length J vector, the initial value of intercept parameters.

cc

A constant constraining the magnitude of the norms of person and item parameter vectors.

tol

The tolerance for convergence with a default value 5.

print_proc

Print the precision during the estimation procedure with a default value TRUE.

Value

The function returns a list with the following components:

theta_hat

The estimated person parameter matrix.

A_hat

The estimated loading parameter matrix

d_hat

The estimated intercept parameters.

References

Chen, Y., Li, X., & Zhang, S. (2018). Joint Maximum Likelihood Estimation for High-Dimensional Exploratory Item Factor Analysis. Psychometrika, 1-23. <doi:10.1007/s11336-018-9646-5>;

Examples

# load a simulated dataset
attach(data_sim)

# use all available cores by running
# setMIRTthreads(-1)

# run the exploratory analysis
res <- mirtjml_expr(response, K)