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Inter-rater quantifies the reliability between multiple raters who evaluate a group of subjects. It calculates the group quantity, Fleiss kappa, and it improves on existing software by keeping information about each user and quantifying how each user agreed with the rest of the group. This is accomplished through permutations of user pairs. The software was written in Python, can be run in Linux, and the code is deposited in Zenodo and GitHub. This software can be used for evaluation of inter-rater reliability in systematic reviews, medical diagnosis algorithms, education applications, and others.

License: GNU General Public License v3.0

Python 100.00%
inter-rater systematic-reviews

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inter-rater's Issues

pip package?

Was looking to install via pip.

Please let me know if you need assistance creating pip package. I maintain one for another project currently.

incorrect categorical encoding?

'o' vs '0' number zero

Notice that in the printed output from inter_rater.py example I see the following error.

Number of absent or invalid ratings: 757. Proportion of total: 0.47

Consider how categories and datafile are encoded:

#  categories for ratings (i.e. “benign”, “malignant”; “1”, “0”, “-1”)
categories

array(['1', '0', '-1'], dtype='<U2')
# data file with the Nxn matrix where each row is a subject and each column corresponds to the ratings of one rater.
nparray

array(
      [['-1', 'o', '-1', 'o'],
       ['-1', 'o', '-1', 'o'],
       ['o', 'o', '-1', '-1'],
       ...,
       ['-1', '-1', 'o', 'o'],
       ['-1', 'o', '-1', 'o'],
       ['-1', 'o', 'o', '1']], dtype='<U2')

If the correct encoding is applied to match categories, I will get a different result showing undesirable negative Kappa.

nparray = np.where(nparray=='o','0',nparray)

ymin = -1
ymax = 1

ref: https://arxiv.org/pdf/1809.05731.pdf

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