Table 4.
Akaike information criterion (AIC) differences among the candidate nested models presented in Fig. 3
| Added Risk Factor | Number of Risk Factors | AIC Value | Δi |
|---|---|---|---|
| Preeclampsia | 8 | 108.36 | 4.65 |
| Antihypertensive Medication | 9 | 104.47 | 0.76 |
| Depression Level | 10 | 104.84 | 1.13 |
| Fetal Sex | 11 | 103.71 | 0 |
| Hormones Medication | 12 | 109.62 | 5.91 |
We focus on models from size 8 to 12 risk factors. The AIC difference is calculated as Δi=AICi−AICmin. Starting from values of Δi>4 the level of empirical support of model i, with respect to the best model, is considerably less (see [94] ch.2 for a detailed explanation). We highlight in bold the AIC differences related to the models for which there is a substantial empirical support (i.e. Δi<4)