stats.inter_rater.aggregate_raters()

statsmodels.stats.inter_rater.aggregate_raters

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.