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Materials and methods . Two longitudinal datasets are utilized to address this potential causal association. The first is an ongoing longitudinal survey of 12,686 males and females beginning in 1979 from the National Longitudinal Survey of Youth (NLSY), a nationally representative sample from the United States. In the 1994 follow-up interview, 8,759 adults (age range 29-37 years) had complete data on past-year adult cannabis use and current depression. Individual's probability to use cannabis was predicted through a propensity score approach using over 50 baseline covariates. The second dataset is from an observational prospective cohort study of 2,311 first-grade children enrolled in 1985-1986 as part of the Johns Hopkins University, Prevention Research Center (PRC) randomized trial of classroom-based preventive interventions. In the young adult follow-up interview, 1,494 adults (age range 19-24 years) had complete data on early-onset cannabis problems and young adult major depression. Both studies utilized new causal inference statistical techniques, known broadly as propensity score techniques. Observed confounding covariate differences were controlled through the estimation and application of propensity score techniques. Numerous propensity score techniques exist, yet few guidelines are available to aid researchers in choosing the best technique for a specific dataset and research question. Propensity score estimation and application techniques are described and a taxonomic approach is proposed to guide selection of the best techniques for these data.

Results . In the NLSY dataset, after using propensity score adjustment, the odds of current depression among past-year cannabis users was only 1.1 times higher than the comparison group (95% Confidence Interval (CI): 0.8, 1.7). After applying the best propensity score technique to use for the PRC dataset, the risk of young adult depression for the recent-onset cannabis problem using females was not statistically significantly different from the risk among the comparison females (Odds Ratio (OR): 0.68, 95% CI: 0.20, 2.34). The risk of young adult depression among the early-onset cannabis problem using males was positive, but still not statistically significantly different from the comparison males (OR: 1.72, 95% CI: 0.77, 3.60).

Discussion . Similar inferences may be drawn from both studies testing the potential causal link between cannabis and depression. After adjusting for differences in baseline confounders of cannabis use and depression, past-year cannabis use was not a significant predictor of current depression among adults. For adolescents, although the estimated association was higher for males, the qualitative difference in risk for males and females and the lack of statistical significance for either gender did not support claims of a causal association.

Conclusion . These data do not support the hypothesis that there is a causal link between cannabis and depression.