Table 3.

Additive model (ADD).

	Low risk	High risk
	a1 = 2·a0; a2 = 4·a0	a1 = 5·a0; a2 = 10·a0
	b1 = 5·b0; b2 = 10·b0	b1 = 5·b0; b2 = 10·b0
Theoretical penetrance matrix
Neural network
Mean absolute difference E
Sum	0.2313	0.2059
Logistic regression
Mean absolute difference E
Sum	0.2530	0.2544
Logistic regression (design variables)
Mean absolute difference E
Sum	0.2897	0.2804

Mean absolute differences between theoretical and estimated penetrance matrices from 100 replications in the low and high risk scenario.