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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