SSI 2019 Course Spotlight "Applied Hierarchical Linear Modeling" with Catherine Cubbin
Dr. Catherine Cubbin returns to teach "Applied Hierarchical Linear Modeling" at the 12th annual Summer Statistics Institute
What is the main goal of this course? What makes you excited about teaching this course?
The main goal of this course is to expose students to the myriad ways that HLM can be used to answer important questions and to apply some of the most common approaches by the end of the four days. I love that students come in with specific real-world research questions that they are currently trying to address.
How much background knowledge or experience in this subject is required to be able to follow the course material?
Some knowledge of SAS software and statistics is important, and a curiosity about how “context” influences outcomes for individuals is a huge plus!
What skills and knowledge can participants expect to acquire by the end of the course?
HLM modeling for linear and logistics models, HLM modeling for longitudinal data, and knowing how to determine if an HLM model is warranted, given a specific dataset and study design.
What interested you in teaching this course at the 12th annual SSI?
I like the challenge of taking a semester-length course and paring it down to the essential elements to get students comfortable running and interpreting HLM models. I’m also energized by the diversity of professional backgrounds and ideas among the students.
