|Description: Repeated measures and longitudinal data are ubiquitous; as such, it is incumbent upon the data analyst to take account of any correlations between measurements in the interpretation of these data. This course explores these methods in a detailed manner. Another instance in which correlated measurements may arise is in nested or hierarchical settings in which, for example, more than one sibling within a household is surveyed. Hence, the methods addressed in this course thus allow each individual in a study to serve as his/her own control. Additional important topics which this course may cover include applications to structural equations models (e.g., via the ‘OpenMx’ and/or ‘lavaan’ packages), generalized linear and nonlinear models, growth mixture models and trajectory analysis. In this course, students will analyze real-life data sets using appropriate statistical programs and packages, such as R - R/Studio, SAS, and/or Mplus.