Skip to main content

Python implementation of the R package IRR

Project description

https://github.com/rickdkk/pyirr/actions/workflows/python-app.yml/badge.svg https://zenodo.org/badge/484431981.svg https://img.shields.io/badge/License-GPLv3-blue.svg

Python implementation of the R package IRR, all credit goes to the original authors [1]. The package contains functions to calculate coefficients of Interrater Reliability and Agreement for interval, ordinal and nominal data: intraclass-correlations, Finn-Coefficient, Robinson’s A, Kendall’s W, Cohen’s Kappa, and others. This is a straight line-for-line port from the R-package, so it is not particularly Pythonic and mainly made as an exercise to learn more about R. For documentation I highly recommend you head over to the R package page, they put in a lot of effort for the documentation!

How to install

The package is available on the Python Package Index (PyPI). To install it you can run:

pip install pyirr

How to use

A simple example:

from pyirr import read_data, intraclass_correlation

data = read_data("anxiety")  # loads example data
intraclass_correlation(data, "twoway", "agreement")

Returns:

==================================================
          Intraclass Correlation Results
==================================================
Model: twoway
Type: agreement

Subjects = 20
Raters = 3
ICC(A,1) = 0.20

F-Test, H0: r0 = 0 ; H1 : r0 > 0
F(19.00,39.75) = 1.83, p = 0.0543

95%-Confidence Interval for ICC Population Values:
-0.039 < ICC < 0.494
==================================================

Another simple example:

from pyirr import read_data, kappam_fleiss

data = read_data("anxiety")  # loads example data
kappam_fleiss(data, detail=True)

Returns:

==================================================
            Fleiss` Kappa for m Raters
==================================================
Subjects = 30
  Raters = 6
   Kappa = 0.430

       z = 17.652
 p-value = 0.000

                         Kappa       z  p.value
1. Depression            0.245   5.192      0.0
2. Personality Disorder  0.245   5.192      0.0
3. Schizophrenia         0.520  11.031      0.0
4. Neurosis              0.471   9.994      0.0
5. Other                 0.566  12.009      0.0
==================================================

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

pyirr-0.84.1.2.tar.gz (53.9 kB view hashes)

Uploaded Source

Built Distribution

pyirr-0.84.1.2-py3-none-any.whl (58.9 kB view hashes)

Uploaded Python 3

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page