Table 1.

Fixed effects of LASSO models and hierarchical logistic regression predicting dropout.

variable	LASSO		glm
	intake var	network var	block 1		block 2
	estimate	estimate	estimate	p-value	estimate	p-value
sex	−0.32		−0.79	0.195	−1.27	0.101
GSI	0.43		0.87†	0.066	0.62	0.324
nervous −betweenness		−0.74			−1.00*	0.018
excited-expected force		−0.62			−0.90*	0.035
active-instrength		−0.68			−1.02*	0.035
social support −outstrength		−0.87			−1.00*	0.029
Δ R²McFadden					0.26***	<0.001
R²McFadden			0.06†	0.097	0.32***	<0.001

Note. LASSO = least absolute shrinkage and selection operator; glm = generalized linear model; var. = variables; GSI = Global Severity Index; ^†p ≤ 0.10; *p ≤ 0.05; **p ≤ 0.001.