Major changes in this release include:
- New OscatsSpace and OscatsPoint classes for a unified representation of continuous, binary, and ordinal latent spaces
- Unification of the OscatsContModel and OscatsDiscrModel into a single OscatsModel based on the new latent space representation
- Generalization of OscatsItem to allow any arbitrary number of models for complex simulation studies
- Implementation of the a-Stratified item selection algorithm
- Newly implemented models:
- Partial Credit, Generalized Partial Credit
- Graded Response (Homogenous and Heterogenous Logistic)
- New examples, including implementation of a custom algorithm in Python
Plans for upcoming development include:
- Support for simultaneous testing of multiple examinees
- Exposure control and item selection constraints
- R Bindings
- Support for GObject Introspection
- Example integration with Concerto for CAT administration