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Mixed Models with R

September 21 @ 1:00 pm - 5:00 pm

Modern Languages Building (MLB), Room 2001A

Mixed models are an extremely useful modeling tool for situations in which there is some dependency among observations in the data, where the correlation typically arises from the observations being clustered in some way. For example, it is quite common to have data in which we have repeated measurements for the units of observation, or in which the units of observation are otherwise clustered (e.g. students within school, cities within geographic region). While there are different ways to approach such a situation, mixed models are a very common and powerful tool to do so.  In addition, they have ties to other statistical approaches that further expand their applicability.
 
The goal of this workshop is primarily to provide a sense of when one would use mixed models and how to incorporate a variety of standard techniques.  It is very applied in nature, and only assumes a basic understanding of standard regression models (and use of R for such models).

REGISTRATION

To register for CSCAR Workshops, call the CSCAR front desk at (734) 764-7828 or come to the office in person with cash or check or a UM department shortcode:

OFFICE HOURS

9:00 a.m. – 5:00 p.m., Monday through Friday
Closed 12pm – 1:00 p.m. every Tuesday for staff meeting.
Voice: (734) 764-7828 (4-STAT from a campus phone)
Fax: (734) 647-2440

ADDRESS

Consulting for Statistics, Computing and Analytics Research (CSCAR)
The University of Michigan
3550 Rackham
915 E. Washington St.
Ann Arbor, MI 48109-1070

Details

Date:
September 21
Time:
1:00 pm - 5:00 pm
Event Category:

Other

Prerequisite
The goal of this workshop is primarily to provide a sense of when one would use mixed models and how to incorporate a variety of standard techniques. It is very applied in nature, and only assumes a basic understanding of standard regression models (and use of R for such models).
Class size
24 participants, 1 per computer
U-M Affiliated Fee
189
Not U-M Affiliated Fee
420
Register
Instructors
Michael Clark