 Data Analysis for Specific Aim 1: Analyses investigating group differences in alcohol problems and treatment utilization will use random coefficient models Raudenbush Bryk, 2002; Singer Willett, 2003. Investigators will construct longitudinal models using the following sequence of analytic steps recommended by Singer and Willett 2003: 1 examine empirical growth plots; 2 fit an unconditional means model; 3 fit an unconditional linear growth model; 4 fit an unconditional non-linear model e.g., piecewise model; 5 determine the best model of longitudinal change by comparing models in the previous two steps using the Akaike information criterion AIC; f select the most appropriate error covariance structure using AIC; and 6 add level-2 predictors e.g., intervention conditions. Models for binary outcomes e.g., treatment utilization will use generalized linear mixed-effects models assuming a binary distribution with a logistic link function. 