GDINA: ILCA – R documentation

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ILCA

Iterative latent-class analysis

Description

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

Usage

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.

Author(s)

Zhehan Jiang, The University of Alabama

References

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

Examples

## Not run: 
ILCA(sim10GDINA$simdat, sim10GDINA$simQ)

## End(Not run)

GDINA

The Generalized DINA Model Framework

v2.8.0

GPL-3

Authors

Wenchao Ma [aut, cre, cph], Jimmy de la Torre [aut, cph], Miguel Sorrel [ctb], Zhehan Jiang [ctb]

Initial release

2020-05-23