Subsequently, the 2 class, 1 factor mixture model was run with covariates, with class membership and the factor regressed on all covariates simultaneously. In Mplus, factor mixture modelling with covariates takes into account the uncertainty of group membership by using posterior class membership probabilities instead of taking class membership to be certain. A more conservative alpha level of p<0.01 was used to correct for testing multiple effects. The covariates were selected because the research literature indicates that they are associated with long-term opioid dependence: age, male sex, a measure of opioid use (times per day during heaviest period of use); suicide attempts; other substance dependence diagnoses; and mental health variables (depression, PTSD, ASPD and BPD) [1, 46-48]. Some variables (alcohol, nicotine and stimulant dependence, employment status, and panic disorder) were removed from the final model because they had not been significant in earlier models. All analyses were conducted in Mplus version 5.0 [49].
