Time-varying effect modeling (TVEM) is a novel method that enables health, behavioral, and social scientists to examine developmental (i.e., age-varying) and dynamic (i.e., time-varying) associations. TVEM estimates regression coefficients as non-parametric functions of continuous age or time. This method can be applied to existing cross-sectional or longitudinal data to answer novel questions such as: How does the association between a particular contextual risk factor and health behavior vary across age? How do these complex associations differ across population subgroups? TVEM also can be applied to intensive longitudinal data such as ecological momentary assessments to reveal dynamic processes, addressing questions such as: How does the association between mood and craving unfold with time during a smoking quit attempt? The goal of this talk is to describe research questions that can be addressed by applying TVEM to existing data, and to provide resources for researchers interested in using the models in their own work.