Model fit
Model fit was assessed using a variety of fit measures, including both absolute and incremental fit indices as recommended by Hu and Bentler (1999). Fit indices to test the parallel process LGM were the χ2-test, comparative fit index (CFI), root mean square error of approximation (RMSEA), and Akaike information criterion (AIC). The AIC quantifies the relative goodness of fit, examining the complexity of the model together with its goodness of fit to the sample data to produce a balanced measure. The preferred model is that with the lowest AIC value. CFI values above .95 suggest good fit ( Hu & Bentler, 1999), RMSEA values below .08 suggest adequate fit, and values below .06 suggest good fit ( Hu & Bentler, 1999). Strength of effects were examined by looking at the significance of parameter estimates at the p < .05 level and by examination of effect size following Cohen's d estimations where d = .20, .50, and .80 for small, medium, and large effects ( Cohen, 1988). We report standardized values in all models. To account for multiple comparisons, alpha was set at p < .01 for all path coefficients.