Table 2.
AUC (95% CI) | |||
---|---|---|---|
Logistic | Elastic net | Random forest | |
Binge-eating abstinence | |||
10 repeated CV | 0.50 (0.48–0.52) | 0.51 (0.48–0.53) | 0.49 (0.47–0.52) |
Bootstrap | 0.50 (0.49–0.52) | 0.53 (0.52–0.54) | 0.50 (0.49–0.51) |
Optimism bootstrap | 0.60 (0.59–0.61) | 0.59 (0.58–0.60) | 0.93 (0.92–0.94) |
Weight loss ⩾5% | |||
10 repeated CV | 0.66 (0.64–0.69) | 0.68 (0.66–0.70) | 0.59 (0.56–0.61) |
Bootstrap | 0.61 (0.59–0.62) | 0.63 (0.62–0.65) | 0.56 (0.55–0.57) |
Optimism bootstrap | 0.71 (0.70–0.73) | 0.73 (0.72–0.74) | 0.94 (0.93–0.95) |
RMSE (95% CI) | R2 (95% CI) | |||||
---|---|---|---|---|---|---|
Linear | Elastic net | Random forest | Linear | Elastic net | Random forest | |
Binge-eating reduction % (log) | ||||||
10 repeated CV | 0.42 (0.36–0.48) | 0.29 (0.22–0.36) | 0.28 (0.21–0.35) | 0.04 (0.03–0.05) | 0.04 (0.03–0.05) | 0.05 (0.04–0.06) |
Bootstrap | 0.53 (0.50–0.57) | 0.35 (0.30–0.40) | 0.35 (0.30–0.40) | 0.012 (0.008–0.015) | 0.012 (0.008–0.015) | 0.011 (0.009–0.013) |
Optimism bootstrap | 0.51 (0.48–0.55) | 0.48 (0.44–0.52) | 0.37 (0.32–0.42) | 0.009 (0.007–0.013) | 0.049 (0.048–0.052) | 0.634 (0.632–0.636) |
Eating-disorder psychopathology | ||||||
10 repeated CV | 0.81 (0.79–0.84) | 0.73 (0.71–0.75) | 0.73 (0.71–0.76) | 0.18 (0.15–0.21) | 0.27 (0.24–0.30) | 0.25 (0.22–0.28) |
Bootstrap | 0.91 (0.90–0.93) | 0.74 (0.73–0.75) | 0.75 (0.74–0.76) | 0.12 (0.10–0.13) | 0.23 (0.21–0.24) | 0.21 (0.20–0.23) |
Optimism bootstrap | 0.81 (0.79–0.82) | 0.74 (0.73–0.75) | 0.61 (0.60–0.62) | 0.17 (0.16–0.19) | 0.23 (0.22–0.24) | 0.63 (0.62–0.64) |
Weight loss % | ||||||
10 repeated CV | 7.39 (7.18–7.59) | 7.19 (6.97–7.41) | 7.07 (6.90–7.24) | 0.12 (0.10–0.14) | 0.12 (0.10–0.15) | 0.05 (0.04–0.07) |
Bootstrap | 8.29 (8.15–8.43) | 7.61 (7.48–7.74) | 7.30 (7.19–7.42) | 0.07 (0.06–0.08) | 0.056 (0.047–0.065) | 0.021 (0.017–0.026) |
Optimism bootstrap | 7.34 (7.20–7.48) | 7.08 (6.95–7.21) | 5.88 (5.78–6.02) | 0.10 (0.09–0.11) | 0.10 (0.09–0.11) | 0.592 (0.586–0.594) |
AUC. area under the receiver operator characteristic curve; RMSE, root mean square error, 10 repeated CV, repeated 10-fold cross-validation.
Note: Higher AUC values indicate greater predictive accuracy; lower RMSE values and higher R2 values indicate greater predictive accuracy.