Parameter Estimation in Probabilistic Knowledge Structures

This app illustrates parameter estimation in probabilistic knowledge structures. After a short overview of three estimation procedures, the user can enter observed response frequencies and the assumed knowledge structure for four items. Parameters are then estimated, using the Maximum Likelihood (ML), Minimum Discrepancy (MD) and MDML method. The app also tells the user whether the entered knowledge structure is valid and whether the estimation procedure converged and yielded identifiable parameter estimates.


TquanT is co-funded by the Erasmus+ Programme of the European Commission.

This server is powered by RStudio's Shiny Server Open Source.

© 2016, 2017, Claudia Glemser, University of Tübingen, Germany

Legal Disclaimer