lower ends of the spectrum, which may have resulted in lowered power. Second, previously reported findings are often based on univariate/bivariate analysis although pre-intervention drinking levels are generally known to be confounded with other individual and situational factors (e.g., gender). Treatment groups are typically balanced using random assignment on measured and unmeasured variables. However, any covariates that are strongly related to outcomes need to be adjusted in examining treatment effects (Pocock et al., 2002). This recommendation is also applicable for examining moderation effects. Thus, adjusting for individual and situational factors related to treatment outcomes may help clarify whether pre-intervention drinking levels affect the efficacy of a PFI above and beyond the influences of these confounding factors. Third, some of the existing studies categorized students based on an a priori definition (e.g., those with five or more drinks in a row in the past 2 weeks, or those in the upper half of a sample based on drinks). However, this heuristic dichotomization approach may be arbitrary. In recent studies of natural trajectories of alcohol use among adolescents and college students, heterogeneous subgroups are empirically identified based on their trajectories over time (e.g., Sher, Gotham, & Watson, 2004). The same methodology may
