Table 3:

Information-theoretic model fit statistics for growth models as predictors of cumulative alcohol use

	Log-likelihood			BIC
	Baseline	Intercept	Int/Slopes	Baseline	Intercept	Int/Slopes
PC1	−129808.6	−129801.6	−129762.2	259887.6	259880.7	259816.5
PC2	−126267.5	−126255.4		252805.3	252788.3
PC3	−127815.3	−127809.0	−127753.8	255900.9	255895.6	255799.8
PC4	−132220.3	−132219.8	−132168.1	264710.8	264717.1	264628.4
PC5	−128900.1	−128899.9	−128865.7	258070.5	258077.4	258023.6
PC6	−129724.4	−129723.4		259719.1	259724.4

Note: Model fit statistics for three different models predicting cumulative alcohol use. BIC is Schwarz’s Bayesian Information Criterion (Schwarz, 1978). The Baseline model includes growth curve parameters (plus the mean and variance for cumulative drinking). The Intercept model includes the piecewise linear model intercept as a predictor of cumulative drinking through age 24 (one additional parameter), whereas the Int/Slopes model includes both slopes as predictors of drinking as well (three additional parameters relative to the Baseline model). The model best supported by the evidence for each component is highlighted in gray.