Applied Multilevel Modeling
Credits: 4.0
Term: Spring 2023 - Full Term (01/24/2023 - 05/08/2023)
Grade Mode: Letter Grading
Term: Spring 2023 - Full Term (01/24/2023 - 05/08/2023)
Grade Mode: Letter Grading
Class Size:
20
CRN: 56026
CRN: 56026
This applied course in multilevel modeling is designed for graduate students in education and the social sciences who are interested in conducting statistical analysis to answer questions about (1) contextual effects on individual outcomes, and (2) individual change over time. Topics addressed include exploratory analyses of multilevel data, conditional and unconditional models, fixed and random effects, model assumptions, model fit, non-linear change, discontinuous change, time-varying predictors, unequally spaced measurement occasions, and three-level multilevel models. Prereq: EDUC 978 or the equivalent.
Registration Approval Required. Contact Instructor or Academic Department for permission then register through Webcat.
Instructors: Suzanne Graham
Times & Locations
Start Date | End Date | Days | Time | Location |
---|---|---|---|---|
1/24/2023 | 5/8/2023 | M | 4:10pm - 6:30pm | MURK 102 |