This seminar provides an introduction to multilevel modeling. Multilevel models, also known as mixed, hierarchical, and random-effects models, provide a conceptual framework and an analytic option for working with clustered/nested data (Aarts, Verhage, Veenvliet, Dolan, & van der Sluis, 2014). They allow researchers to study different sources of variation in the outcomes, and the effects of predictors at different and across levels.

This seminar will consider the formulation of statistical models for multilevel modeling applications. The presentations will be conceptual and the instructor will demonstrate analyses using personal computers and provide time for “hands on” practice. We will use the software programs HLM8 (Raudenbush, Bryk, Cheong, Congdon, & Du Toit, 2019), the lmer4 R (Bates, Maechler, B., & Walker, 2015) and the WinBUGS (Lunn, Thomas, Best, & Spiegelhalter, 2000) packages, and SPSS in the seminar. The prerequisite for this seminar is a course on multiple regression.

• Class Hours: Tuesdays 9:40 am to 12:35 pm 
• This class will meet synchronously