Version 1.0-0 of DAKS (Data Analysis and Knowledge Spaces) has been
released to CRAN.
Knowledge space theory is a recent psychometric test theory based on
combinatorial mathematical structures (order and lattice theory).
Solvability dependencies between dichotomous test items play an
important role in knowledge space theory. Utilizing hypothesized
dependencies between items, knowledge space theory has been
successfully applied for the computerized, adaptive assessment and
training of knowledge.
The package DAKS implements inductive item tree analysis methods for
deriving surmise relations from binary data. It provides functions for
computing population and estimated asymptotic variances of the used
fit measures, and for switching between test item and knowledge state
representations. Other features are a Hasse diagram drawing device, a
data simulation tool based on a finite mixture latent variable model,
and a function for computing response pattern and knowledge state
frequencies.
Best regards,
Anatol Sargin
Ali Uenlue
--
Department of Computer-Oriented Statistics and Data Analysis
Institute of Mathematics
University of Augsburg
http://stats.math.uni-augsburg.de/
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