Statistical Methods
At baseline we summarized the demographic characteristics of men grouped by SL and CC. An analytic model with a random neighborhood intercept tested for differences between SL and CC at baseline.We examined the effects of dropout by comparing the baseline characteristics of men who were retained at 6 months (Mixed-effects random intercept linear and logistic longitudinal models were used to assess the intervention’s effect at 6 months for continuous and binary outcomes respectively. Both models had random effects for participants and for neighborhoods. For measures that were only collected at 6 months, we omitted the individual random effect from the model, but kept the random effects for the neighborhood. The intervention effect is estimated as a difference (SL minus CC) of differences (6-months estimate minus baseline estimate) when we have baseline and 6 month data. When we only had data at the 6 months assessment, we calculated the difference of SL minus CC (i.e., the RDT for mandrax and self-reports of community engagement).