Iterative latent-class analysis

This function implements an iterative latent class analysis (ILCA; Jiang, 2019) approach to estimating attributes for cognitive diagnosis.

ILCA(dat, Q, seed.num = 5)

Arguments

dat

A required binary item response matrix.

Q

A required binary item and attribute association matrix.

seed.num

seed number; Default = 5.

Value

Estimated attribute profiles.

References

Jiang, Z. (2019). Using the iterative latent-class analysis approach to improve attribute accuracy in diagnostic classification models. Behavior research methods, 1-10.

Author

Zhehan Jiang, Peking University

Examples

if (FALSE) { # \dontrun{
ILCA(sim10GDINA$simdat, sim10GDINA$simQ)
} # }