The next step was to add Treatment to the LGM, as a predictor of the slope and intercept latent variables. Treatment was coded as contrast dummy variables and tested sequentially in the LGM. The best fitting model contained Treatment coded as a contrast of NS v. CaseM and NS+CM. With this treatment contrast the model had a chi-square of 54.38 (df=44; p > .10). The treatment contrast was significantly and positively associated with the intercept of PDA (B =.29; z = 2.02, p < .05), and with the slope of PDA (B =.35; z = 2.33, p < .05), indicating that NS (in contrast to the other two conditions) contributed significantly to both the level of PDA at 3 months (posttreatment), and to the increase in PDA over time.
