IFAS Statistics

Applied Linear Mixed Models

Course Description

Analysis of data from designed experiments and observational studies often involve both fixed and random effects; that is, the studies have mixed effects. Perhaps the simplest mixed effects model is that for a randomized complete block design. As is the case for all mixed models, the model for the randomized complete block design has an underlying covariance structure associated with the response variable. This covariance of the response is generally partitioned into the covariance matrix G assocated with the modeled random effects and the covariance structure of the residuals, R. Given a set of data, determining the appropriate structure for these covariance matrices is both important and challenging. This short course will focus on the process of modeling G and R using real data sets. Topics include a review of covariance structures available in SAS, using the estimated covariance matrix to guide in the choice of covariance structure, accounting for spatial variation in either covariates or errors, and incorporating radial smoothing in the analysis. Methods for asessing the fit of the model and new multiple comparison methods will be presented. This two-day workshop will introduce participants to SAS's PROC MIXED and PROC GLIMMIX. Participants will have the opportunity to analyze data sets that illustrate the methods discussed during the class. Extensive use will be made of real-data sets throughout the course.

Who should come

This workshop is targeted toward those who have some experience with design of experiments and who want to learn more about mixed models. After this workshop, participants should be able to analyze normal data arising from studies with mixed effects.

Instructor

Dr. Linda J. Young, Professor in UF’s Department of Statistics, has consulted with researchers on the faculties of Oklahoma State University, University of Nebraska, and University of Florida. Her research interests are in sampling and modeling of ecological and environmental data.

Registration

To register for a workshop please contact Allison Pipkin at apipkin@stat.ufl.edu or 352.392.1946. Cash or check (payable to University of Florida) is accepted; or Department Fund Transfer (E2R).Click here to register for the this workshop online.

Fee

The cost of the workshop is $500 - accept cash or check (payable to University of Florida); or Department Fund Transfer (E2R).

Dates for workshop

The workshop will take place on the following dates

Date	Location	Time
14-15, December 2009	Conference room 426 of McCarty Hall, Building C	2 day workshop (8am - 5pm)