• Department
  • Undergraduate Program
  • Graduate Program
  • People
  • Research
  • GIVE
  • PSYCHOLOGY 205D    Section: 1

    MULTILEVEL MODELS

    Spring Quarter 2007

    Units: 4
    Prerequisites:
    Hierarchical data arise from a variety of situations: studies of clustered data (e.g., students nested within classrooms, patients nested within clinics), repeated measures where observations are nested within individuals (e.g., learning, reading), longitudinal data (repeated observations over time), and spatially correlated data (e.g., individuals nested within geographic settings). This course concerns multilevel analysis of normal, hierarchically structured data, including cross-sectional clustered data, repeated measures, and longitudinal data. Broadly, topics include hierarchical linear and nonlinear models and latent curve models. Will will also consider how these methods may be used to handle unbalanced and missing data.

    Text(s):

    Textbook Information not Available Yet
    Classroom Class Schedule Course Website
    157 Young W   9:00 AM - 1:00 PM
    Instructor Instructor Email Office Office Hours
    Shelley Blozis , Ph.D. 174F Young Hall Wed 2pm-5pm