IRT
Item Response Theory in Python
Currently contains simple code, using a 4-parameter model, and allowing for partial credit.
The parameter estimation is done using MMLE with parameter regulation, and the underlying optimization uses scipy.optimize
estimate_thetas receives an input array, where each line represents the scores of a single person in each question, and returns the estimated theta parameters per person and the model parameters per question.
1 maintainer
Release files for irt 0.0.2
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Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| irt-0.0.2.tar.gz | 5.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| irt-0.0.2-py2.py3-none-any.whl | Python 2, Python 3 | none | any | Details |
Total release size:15.1 kB
Release files / irt-0.0.2.tar.gz
| Download URL | irt-0.0.2.tar.gz |
|---|---|
| Size | 5.3 kB |
| Tags | Source |
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twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/2.7.14
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Release files / irt-0.0.2-py2.py3-none-any.whl
| Download URL | irt-0.0.2-py2.py3-none-any.whl |
|---|---|
| Size | 9.8 kB |
| Tags | Python 2 Python 3 |
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twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/40.8.0 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/2.7.14
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