Table 3. Evaluation of logistic regression (Wald test) and leave-one-out cross-validation (LOOCV) error.

Model: $l={\beta }_0+{\beta }_1{x}_1+{\beta }_2{x}_1^2$ where $x_1:$ average MAP (n = 103 patients)
LOOCV: average observed accuracy = 0.66; average kappa statistic = 0.334
Predictor	Coef. estimate (logit)	Std. error	z-Value	p-Value
Intercept	${\beta }_0$= –0.55	0.242	–2.293	0.02183*
Average MAP ($x_1$)	${\beta }_1$= 8.62	2.944	2.931	0.00338**
Average MAP ($x_1^2$)	${\beta }_2$= –7.601	3.039	–2.501	0.0123*

*p < 0.05; **p < 0.01.