Chance-corrected Agreement Coefficients
=======================================
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The **irrCAC** is a Python package that provides several functions for
calculating various chance-corrected agreement coefficients. This package
closely follows the general framework of inter-rater reliability assessment
presented by Gwet (2014).
The functionality covers calculations for various chance-corrected agreement
coefficients (CAC) among 2 or more raters. Among the CAC coefficients covered
are Cohen's kappa, Conger's kappa, Fleiss' kappa, Brennan-Prediger coefficient,
Gwet's AC1/AC2 coefficients, and Krippendorff's alpha. Multiple sets of weights
are proposed for computing weighted analyses.
The functions included in this package can handle 2 types of input data. Those
types with the corresponding coefficients are in the following list:
1. Contingency Table
1. Brennar-Prediger
2. Cohen's kappa
3. Gwet AC1/AC2
4. Krippendorff's Alpha
5. Percent Agreement
6. Schott's Pi
2. Raw Data
1. Fleiss' kappa
2. Gwet AC1/AC2
3. Krippendorff's Alpha
4. Conger's kappa
5. Brennar-Prediger
.. note::
All of these statistical procedures are described in details in
Gwet, K.L. (2014,ISBN:978-0970806284):
"Handbook of Inter-Rater Reliability," 4th edition, Advanced Analytics, LLC.
This package is a port *(with permission)* to Python of the
`irrCAC <https://github.com/kgwet/irrCAC>`_ library for R by Gwet, K.L.
.. important::
This is a **work in progress** and *does not* have (yet) the full
functionality found in the R library.
Installation
------------
To install the package, run:
.. code:: bash
pip install irrCAC
Developers
----------
To use the code for development it is recommended to install
`poetry <https://python-poetry.org/>`_ and run:
.. code:: bash
poetry install
And add the `pre-commit` hook:
.. code:: bash
pre-commit install
and update the hooks:
.. code:: bash
pre-commit autoupdate
To update the project dependencies, run:
.. code:: bash
poetry update
Next run the tests:
.. code:: bash
poetry run pytest
There is also a config file for `tox <https://tox.readthedocs.io/en/latest/>`_
so you can automatically run the tests for various python versions like this:
.. code:: bash
tox
Documentation
-------------
The documentation of the project is available at the following page:
http://irrcac.readthedocs.io/
Raw data
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"description": "Chance-corrected Agreement Coefficients\n=======================================\n\n.. image:: https://readthedocs.org/projects/irrcac/badge/?version=latest\n :target: https://irrcac.readthedocs.io/en/latest/?badge=latest\n :alt: Documentation Status\n\n.. image:: https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white\n :target: https://github.com/pre-commit/pre-commit\n :alt: pre-commit\n\n.. image:: https://img.shields.io/badge/code%20style-black-000000.svg\n :target: https://github.com/psf/black\n\nThe **irrCAC** is a Python package that provides several functions for\ncalculating various chance-corrected agreement coefficients. This package\nclosely follows the general framework of inter-rater reliability assessment\npresented by Gwet (2014).\n\nThe functionality covers calculations for various chance-corrected agreement\ncoefficients (CAC) among 2 or more raters. Among the CAC coefficients covered\nare Cohen's kappa, Conger's kappa, Fleiss' kappa, Brennan-Prediger coefficient,\nGwet's AC1/AC2 coefficients, and Krippendorff's alpha. Multiple sets of weights\nare proposed for computing weighted analyses.\n\nThe functions included in this package can handle 2 types of input data. Those\ntypes with the corresponding coefficients are in the following list:\n\n1. Contingency Table\n\n 1. Brennar-Prediger\n 2. Cohen's kappa\n 3. Gwet AC1/AC2\n 4. Krippendorff's Alpha\n 5. Percent Agreement\n 6. Schott's Pi\n\n2. Raw Data\n\n 1. Fleiss' kappa\n 2. Gwet AC1/AC2\n 3. Krippendorff's Alpha\n 4. Conger's kappa\n 5. Brennar-Prediger\n\n.. note::\n All of these statistical procedures are described in details in\n Gwet, K.L. (2014,ISBN:978-0970806284):\n \"Handbook of Inter-Rater Reliability,\" 4th edition, Advanced Analytics, LLC.\n\n This package is a port *(with permission)* to Python of the\n `irrCAC <https://github.com/kgwet/irrCAC>`_ library for R by Gwet, K.L.\n\n.. important::\n This is a **work in progress** and *does not* have (yet) the full\n functionality found in the R library.\n\nInstallation\n------------\nTo install the package, run:\n\n.. code:: bash\n\n pip install irrCAC\n\nDevelopers\n----------\nTo use the code for development it is recommended to install\n`poetry <https://python-poetry.org/>`_ and run:\n\n.. code:: bash\n\n poetry install\n\nAnd add the `pre-commit` hook:\n\n.. code:: bash\n\n pre-commit install\n\nand update the hooks:\n\n.. code:: bash\n\n pre-commit autoupdate\n\nTo update the project dependencies, run:\n\n.. code:: bash\n\n poetry update\n\nNext run the tests:\n\n.. code:: bash\n\n poetry run pytest\n\nThere is also a config file for `tox <https://tox.readthedocs.io/en/latest/>`_\nso you can automatically run the tests for various python versions like this:\n\n.. code:: bash\n\n tox\n\nDocumentation\n-------------\nThe documentation of the project is available at the following page:\nhttp://irrcac.readthedocs.io/\n",
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