Multifinality, equifinality, and fanning are important developmental concepts that emphasize understanding interindividual variability in trajectories over time. However, each concept implies that there are points in a developmental window where interindividual variability is more limited. We illustrate the multifinality concept under…

Hybrid autoregressive-latent growth structural equation models for longitudinal data represent a synthesis of the autoregressive and latent growth modeling frameworks. Although these models are conceptually powerful, in practice they may struggle to separate autoregressive and growth-related processes during estimation. This confounding of change…

Researchers often collect longitudinal data to model change over time in a phenomenon of interest. Inevitably, there will be some variation across individuals in specific time intervals between assessments. In this simulation study of growth curve modeling, we investigate how ignoring individual differences in time points when modeling change over…

Planned missing data designs allow researchers to increase the amount and quality of data collected in a single study. Unfortunately, the effect of planned missing data designs on power is not straightforward. Under certain conditions using a planned missing design will increase power, whereas in other situations using a planned missing design…

Do interventions work and for whom? For this article, we examined the influence of population heterogeneity on power in designing and evaluating interventions. On the basis of Monte Carlo simulations in Study 1, we demonstrated that the power to detect the overall intervention effect is lower for a mixture of two subpopulations than for a…

This study presents a new approach to estimation of a nonlinear growth curve component with fixed and random effects in multilevel modeling. This approach can be used to estimate change in longitudinal data, such as day-of-the-week fluctuation. The motivation of the new approach is to avoid spurious estimates in a random coefficient regression…