Table 6 Goodness of Fit results of the best fitting model validation analysis: 5-fold cross-validation
From: Prediction of the SF-6D utility score from Lung cancer FACT-L: a mapping study in China
| ย | (1)RMSE | (2)MAE | (3)CCC | (4) AEโ>โ0.1 (%) | (5)AEโ>โ0.05 (%) | ARV |
|---|---|---|---|---|---|---|
OLS M4 | 0.0856 | 0.0665 | 0.8186 | 53.60 | 22.08 | 3.9 |
OLS M5 | 0.0854 | 0.0665 | 0.8194 | 54.24 | 22.40 | 4.3 |
TOBIT M4 | 0.0859 | 0.0666 | 0.8222 | 54.56 | 22.24 | 5.2 |
TOBIT M5 | 0.0857 | 0.0667 | 0.8230 | 54.08 | 22.40 | 4.6 |
OPROBIT M4 | 0.0857 | 0.0667 | 0.8185 | 54.72 | 22.56 | 6.9 |
OPROBIT M5 | 0.0854 | 0.0655 | 0.8197 | 53.44 | 21.76 | 2.1 |
BETAMIX M3a | 0.0853 | 0.0661 | 0.8194 | 54.24 | 20.8 | 2.8 |
BETAMIX M4a | 0.0858 | 0.0667 | 0.8176 | 54.88 | 18.88 | 6.2 |