Examples and demos
You can browse through the examples below. Each example has code and outputs, as well as links to download a script to run locally or to view as a Jupyter notebook on NBViewer. Some of the examples have interactive plots, and these will not currently work unless the scripts are run locally. TODO: Add binder links to examples.
If you would like to run the examples as Jupyter notebooks locally to see interactive plots inline with the code, you can clone the repository and run docs/build_nbs.jl like so:
$ git clone https://github.com/JuliaPsychometricsBazaar/ComputerAdaptiveTesting.jl.git
$ cd ComputerAdaptiveTesting
$ julia --project=. docs/build_nbs.jlExamples
|
This example shows how to run a CAT based on a synthetic correct/incorrect 3PL IRT model. |
|
This example shows how to run a CAT based on a synthetic correct/incorrect MIRT model. |
|
Typically, the logistic c.d.f. is used as the transfer function in IRT. However, it in an IRT context, a scaled version intended to be close to a normal c.d.f. is often used. The main advantage is that this is usually faster to compute. ComputerAdaptiveTesting provides normalscaledlogistic, which is also used by default, for this purpose: |
|
Perf plots |
|
This example shows how to run a CAT end-to-end on real data. |