Description
Multilevel Models for Longitudinal Data is a four-day workshop focused on the application and interpretation of multilevel models, also known as hierarchical linear models and mixed models, to repeated measures data. The analysis of longitudinal data (i.e., the repeated measurement of the same cases over time) is fundamental in nearly all areas of social and behavioral science research. Multilevel models provide a natural framework within which to account for dependence of observations within person over time, describe and predict within-person versus between-person variability, and model individual differences in stability and change over time (e.g., fit growth models). Participants in this workshop will learn how to conceptualize, specify, apply, and interpret a variety of MLMs for repeated measures data.
