NYU Steinhardt

Multi-Level Modeling: Nested and Longitudinal Data

  • Course Number: APSTA-GE 2042
  • Hours: 21
  • Units: 2
  • Description: This is a course on models for multi-level nested data. These data arise in nested designs, which are quite common to education & applied social, behavioral & policy science. Traditional methods, such as OSL regression, are not appropriate in this setting, as they fail to model the complex correlational structure that is induced by these designs. Proper inference requires that we include aspects of the design in the model itself. Moreover, these more sophisticated techniques allow the researcher to learn new & important characteristics of the social & behavioral processes under study. In this module, we will develop & fit a set of models for nested designs (these are sometimes called hierarchical linear models). The course assignments will use state of the art statistical software to explore, fit and interpret the models.
  • Old Course Number: E10.2042