Causal models of adolescent substance use: an examination of gender differences using distribution-free estimators.

Abstract

On the basis of previous literature (Hays, Widaman, DiMatteo, & Stacey, 1987; Huba, Wingard, & Bentler, 1981), four alternative causal models of substance use were specified, estimated, and evaluated for adequacy of statistical fit for samples of White male (N = 9,164) and female (N = 8,421) adolescents. Results supported the adequacy of a four-variable simplex model, in which alcohol use predicted marijuana use, and marijuana use predicted enhancer and dampener hard drug use. The four-variable simplex model was robust across the male and female adolescent samples. In addition, we found comparisons of maximum likelihood and asymptotically distribution-free estimators to be relatively robust across the causal models specified with respect to the magnitude of the parameter estimates, and with respect to the significance levels of the critical ratios, although chi-square model fit statistics for the maximum likelihood estimates were highly inflated.