We report the full connected-linear model that is the most unrestricted account of the data (i.e., has five slopes), but this model is likely unnecessarily complicated. To compare models, we take into account the fit statistics of loglikelihood (LL), Akaike’s Information Criterion (AIC), and Bayesian Information Criterion (BIC). In each case, statistics that are closer to zero indicate better model fit. LL represents the absolute amount of misfit between the model and the actual data whereas AIC and BIC take into account both misfit and model parsimony with BIC weighting parsimony to a greater extent. Preferred models are selected on the basis of AIC and BIC and interpreted for each outcome. In cases where AIC and BIC differed, we report and examine both models, but place emphasis on the BIC preferred model as BIC represents a more parsimonious account of the data (Kline, 2011; Vrieze, 2012). We take this approach in order to balance the strengths and weaknesses of connected-linear models. A strength of connected-linear models is that age-specific developmental trends can be identified, but an associated weakness is that
