The study sample size was calculated for a Hierarchical Linear Model (HLM) in which the primary outcome (changes in depressive symptoms severity) was the dependent variable. Using Mplus, the investigators determined that a sample of 90 participants was needed to reach a power of .80. In this power analysis, the correlation between the intercept and the slope was specified to be -0.4. The average slope was assumed to be negative, as depression scores are expected to drop, and was specified as -0.5. To simplify the model, the variances of the intercept, slope, and scores of all the variables in the model (depressive symptoms severity, and covariates) were specified as 1, so as to have the standardized model solution. The treatment effect on the slope (standardized Beta) was specified as 0.45. This corresponds to a medium-to-large effect size (Cohen, 1992). In addition, the effect of two covariates was included. The effect of each of the covariates on the slope was specified as 0.1. The correlation between treatment and each covariate was specified as 0.1, and the correlation between covariates was specified as 0.3.