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 simple noise in the data can appear as meaningful developmental differences. Connected-linear models are subject to overparameterization that leaves the developmental trend jagged and somewhat difficult to interpret. Therefore, interpretation of the more parsimonious BIC preferred model can avoid some of these issues. The most straightforward way to avoid these issues is to examine the scatterplots of the data. We plot each outcome based on the associated age and weight the data points based on the weighting scheme described earlier. The preferred connected-linear and continuous exponential models are overlaid on the data to aid interpretation.
