Table 4.

Linear regression models for the effects of group, age and gender over IGF-2 levels.

Predictors	F (df1, df2)	R2	p	β	SD	pβ
Model 1	17.35 (3, 94)	0.36	<0.001	71.96	36.28	0.05
Group				121.74	20.62	<0.001
Age				0.83	0.73	0.258
Gender				20.45	19.33	0.293
Model 2	25.44 (2, 95)	0.35	<0.001	86.86	33.45	0.011
Group				125.97	20.24	<0.001
Age				0.83	0.73	0.332
Model 3	49.96 (1, 96)	0.34	<0.001	116.69	13.45	<0.001
Group				133.17	18.84	<0.001

Linear regression models were performed using the backpropagation method, excluding variables from the model that do not have a significant impact on the variance explained. Df1: degrees of freedom of the independent variables. df2: degrees of freedom of the dependent variable. R²: R-squared. p: p-value of the regression equation of each model. β: beta coefficients. SD: Standard deviation of beta coefficients. p^β = p-value of the beta coefficients. Group is a dichotomic variable formed from mental condition (healthy, depression). Age is a continuous variable. Gender is a dichotomic variable formed from sex (male, female). We show exact p-values for the better understanding of the models.