Using the Statistical Package for the Social Sciences (SPSS), comparisons of items across low and high LR subjects and between baseline and follow up data used dependent samples t-tests for continuous variables, and the Wilcoxon signed ranks test (reported as a Z statistic) for dichotomous items. Relationships between baseline BOLD response contrasts and outcomes were evaluated through scatter plots and with Pearson’s product-moment correlations. Logistic hierarchical and two types of backward elimination regression analyses ( used to evaluate a modest-sized set of prior-selected variables allowing identification of the most robust predictors of outcomes) evaluated Hypothesis 2 regarding whether BOLD response contrast for any ROIs predicted alcohol outcomes above and beyond the variability predicted by LR. This included an augmented backward elimination (ABE) regression (Dunkler et al., 2014) that uses both significance and change-in-estimate criteria to diminish any bias from selecting only one among a set of correlated variables. The alcohol outcomes were not always normally distributed, a problem addressed by square root transformations.
