Researchers are often interested in studying how the timing of a specific event affects concurrent and future development. When faced with such research questions there are multiple statistical models to consider and those models are the focus of this paper as well as their theoretical underpinnings and assumptions regarding the nature of the effect of the event on the developmental process. We discuss three models, all variants of growth models specified within the multilevel modeling framework, which conceptualize the developmental process and the effect of the event in different ways. These models include the growth model with a time-invariant covariate, the growth model with a time-varying covariate, and the spline growth model. After discussing the models in detail, we applied these models to longitudinal data from the Berkeley Growth Study to examine cognitive changes during infancy and the effect of independent sitting on those changes. Results suggest that research conclusions depend on the model chosen and how certain results can be misconstrued unless the model accurately reflects the research questions. Recommendations and additional non-traditional models are discussed.