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Summer 2014 Workshop:
Introduction to Multilevel Models for Longitudinal and Repeated Measures Data

All materials are available for download electronically in one folder here.



Course Materials

5/15 9:00-10:15 Lecture 1: Introduction to Multilevel Models
5/15 10:30-12:00 Example 1: Review of General Linear Models and Repeated Measures ANOVA
5/15 1:00-2:15 Example 1, continued
Lecture 1, continued
5/15 2:30-4:00 Lecture 2: Describing Within-Person Change over Time
Example 2: Random Effects Models for Change
5/16 9:00-10:15 Lecture 2, continued
5/16 10:30-12:00 Lecture 3: Time-Invariant Predictors in Longitudinal Models
Example 3: Time-Invariant Predictors of Change
5/16 1:00-2:15 Lecture 4: Crossed Random Effects for Other Repeated Measures Designs
Example 4: Crossed Subjects and Items
5/16 2:30-4:00 Example 4, continued

Course Pre-Requisites and Objectives:

The course will introduce multilevel models to analyze individual change over time, as well as to analyze trial-level data from repeated measures designs. Examples will be presented in SPSS, SAS, and STATA where possible. Participants should be familiar with general linear models (e.g., regression, ANOVA) prior to attending the course.

Course Requirements:

The course is not being offered for credit formally, but students who wish to obtain course credit will need to arrange for an individual study credit with the instructor (which can occur during the summer or fall as needed). For those students receiving credit, course performance will be evaluated through an individual project demonstrating knowledge of the concepts presented in class. The topic and scope of the project must be approved on an individual basis, but all projects will take the form of a results section, complete with text, tables, and figures. This project will be due via email by the end of the term in which the credit is being assigned. Participants are welcome to submit early and receive feedback before the deadline in order to revise their assignment.

Academic Honesty:

As a reminder, the University has a policy on academic honesty (see the Graduate Studies Bulletin).

Accommodating Disabilities:

Any student in this course who has a disability that may prevent him or her from fully demonstrating his or her abilities should contact me as soon as possible, so that we can discuss accommodations necessary to ensure full participation and facilitate your educational opportunity.