Table 2.

Linear regression models.

	Model	b	p value	R2	R2 adj	LRT (df)	p value
Baseline model I (B1): with CA as regressor
B1	CA	0.44	<0.001	3%	3%
Baseline model II (B2): adding gender to B1
						Compared against B1
B2	Gender	−0.30	<0.001	4%	4%	25.33 (1)	<0.001
Adding RFs and age-14 distress (D14) separately to B2
						Compared against B2
M1	RFs	−0.86	–	20%	19%	297.25 (10)	<0.001
						Compared against B2
M2	D14	0.63	<0.001	23%	23%	357.07 (1)	<0.001
Adding RFs and age-14 distress (D14) together to B2
						Compared against M2
M3	RFs	−0.19	–	24%	23%	22.11 (10)	0.07
						Compared against M1
M3	D14	0.54	<0.001	24%	23%	81.93 (1)	<0.001

There is no p value for the RFs in model M1 and M3, as the bs of the RFs are here summed up to illustrate whether the cumulative effect is positive or negative, but as the RFs are ten individuals regressors there is no cumulative p value.

adj adjusted, LRT Likelihood-ratio test.