Indiana University Bloomington

Education Y639
Multilevel Modeling

Offered: Spring, Every Year
Capacity: 20
Sequence: No
Pre-Requisites: 2 semesters of graduate coursework in statistics.
Algebra Required: For notation, some proofs.
Calculus Required: Used for some concepts and derivations.
Contact Person for Authorization: None
Instructor: Julie Lorah
Days Per Week Offered: 2 days per week, usually Tue/Thu
Recommended follow-up classes: Depends on research interests.
Syllabus: Download Syllabus
Keywords: Multilevel models, mixed modeling, hierarchical linear modeling, random effects models.
Description: This course will introduce students to the theory and practice of multilevel models - an increasingly common technique for dealing with clustered data. Examples for the course will come primarily from the field of education; however, the methods are presented in general and examples are easily extended to many fields. Students will learn to develop, implement, interpret, and report research involving multilevel analyses. Further, students are expected to gain proficiency in SAS as it pertains to multilevel analysis.
Books: Snijders & Bosker (2012). Multilevel analysis. Similar, although more comprehensive would be Raudenbush & Bryk (2002).
Substantive Orientation: Social sciences; however, links to the natural/physical sciences are plentiful.
Statistical Orientation: Frequentist.
Applied/Theoretical: This is an applied course with some theoretical derivation and explanation.
Software: R, SAS
How Software is Used: Computation, some programming, and data analysis.
Problem Sets: Yes, with a mix of theoretical/conceptual/analytic problems and applied, data analysis.
Data Analysis: Yes, for the homework assignments and the final project.
Presentation: Yes, a research paper is required for the final project. Can include methodological or applied perspectives.
Exams: None at present; however, that could change.