Summary of model selection
| Model | Binomial GLM (complementary log–log) | AFT model (Inverse-Weibull) | Cox PH model (stratified by time-since-injury) | |||||||||
| Accuracy (%) | Sensitivity (%) | Specificity (%) | AIC (# predictors) | Accuracy (%) | Sensitivity (%) | Specificity (%) | AIC (# Predictors) | Accuracy (%) | Sensitivity (%) | Specificity (%) | AIC (# predictors) | |
| Models with main effects only | ||||||||||||
| Null model | 64 | 0 | 100 | 356 | 64 | 0 | 100 | 2243 | 64 | 0 | 100 | 1927 |
| Physical examination only | 67 (63) | 35 (31) | 86 (82) | 338 (10) | 63 (62) | 3.1 (0) | 99 (99) | 2262 (10) | 75 (74) | 48 (46) | 92 (91) | 1928 (10) |
| All predictors | 76 (73) | 54 (49) | 89 (87) | 278 (15) | 74 (73) | 45 (43) | 91 (90) | 2164 (15) | 75 (73) | 51 (47) | 90 (88) | 1915 (14) |
| Models including interaction terms | ||||||||||||
| All interactions | 92 (66) | 87 (48) | 96 (77) | 338 (120) | 84 (70) | 66 (46) | 95 (84) | 2167 (120) | 80 (62) | 71 (65) | 85 (67) | 1965 (105) |
| Stepwise selected models | ||||||||||||
| All predictors stepwise | 77 (75) | 57 (53) | 89 (89) | 266 (7) | 73 (72) | 43 (43) | 92 (90) | 2150 (6) | 76 (73) | 54 (47) | 89 (88) | 1901 (5) |
| All interactions stepwise | 78 (75) | 56 (51) | 91 (90) | 263 (8) | 73 (72) | 43 (43) | 92 (90) | 2150 (6) | 75 (70) | 45 (46) | 92 (85) | 1900 (7) |
Pairs of numbers in a cell refer to performance on training and test data, with the upper number showing performance on the training data, and the lower number the cross-validation performance. For AFT and bGLM models, results are only given for the model with the lowest AIC. AIC are presented with number of predictors in their model.
Bolded values indicate the final model used for the RDR Score.
AFT, accelerated failure time; AIC, Akaike information criterion; GLM, generalised linear modelling; PH, proportional hazard.