ACTCD: Asymptotic Classification Theory for Cognitive Diagnosis

Cluster analysis for cognitive diagnosis based on the Asymptotic Classification Theory (Chiu, Douglas & Li, 2009; <doi:10.1007/s11336-009-9125-0>). Given the sample statistic of sum-scores, cluster analysis techniques can be used to classify examinees into latent classes based on their attribute patterns. In addition to the algorithms used to classify data, three labeling approaches are proposed to label clusters so that examinees' attribute profiles can be obtained.

Version:	1.2-0
Depends:	R (≥ 3.1.0), R.methodsS3
Imports:	GDINA, stats, utils
Published:	2018-04-23
Author:	Chia-Yi Chiu (Rutgers, the State University of New Jersey) and Wenchao Ma (The University of Alabama)
Maintainer:	Wenchao Ma <wenchao.ma at ua.edu>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	yes
CRAN checks:	ACTCD results

Documentation:

Reference manual:

ACTCD.pdf

Downloads:

Package source:	ACTCD_1.2-0.tar.gz
Windows binaries:	r-devel: ACTCD_1.2-0.zip, r-release: ACTCD_1.2-0.zip, r-oldrel: ACTCD_1.2-0.zip
macOS binaries:	r-release (arm64): ACTCD_1.2-0.tgz, r-oldrel (arm64): ACTCD_1.2-0.tgz, r-release (x86_64): ACTCD_1.2-0.tgz, r-oldrel (x86_64): ACTCD_1.2-0.tgz
Old sources:	ACTCD archive

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