ILCA {GDINA} | R Documentation |
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)
[Package GDINA version 2.9.4 Index]