Table 3.

Results of the different methods based on the predefined criteria for mapping between the HOOS-12 and Oxford-12

Method	MAE	r2	KS
Linear regression	6.0	0.67	0.07
Tobit regression	6.0	0.67	0.07
Quantile regression	6.0	0.67	0.07
Linear equating	6.2	0.64	0.11
Equipercentile method	6.2	0.63	0.04

The goal was to minimize the MAE (perfect model = 0), have a Kolmogorov-Smirnov distance as close as possible to 0, and have the r² as close as possible to 1. The methods generated similar results for the r² (range 0.63-0.67) and MAE. The KS distance was best with the equating methods (linear equating and equipercentile methods). MAE = mean absolute error; KS = Kolmogorov-Smirnov distance.