statsmodels.stats.inter_rater.aggregate_raters
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statsmodels.stats.inter_rater.aggregate_raters(data, n_cat=None)
[source] -
convert raw data with shape (subject, rater) to (subject, cat_counts)
brings data into correct format for fleiss_kappa
bincount will raise exception if data cannot be converted to integer.
Parameters: data : array_like, 2-Dim
data containing category assignment with subjects in rows and raters in columns.
n_cat : None or int
If None, then the data is converted to integer categories, 0,1,2,...,n_cat-1. Because of the relabeling only category levels with non-zero counts are included. If this is an integer, then the category levels in the data are already assumed to be in integers, 0,1,2,...,n_cat-1. In this case, the returned array may contain columns with zero count, if no subject has been categorized with this level.
Returns: arr : nd_array, (n_rows, n_cat)
Contains counts of raters that assigned a category level to individuals. Subjects are in rows, category levels in columns.
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