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Special Course Announcement
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Exact Inference on Repeated Measures, Growth Curves,MANOVA and Mixed Models
August 10,2001 Atlanta, GA
Course Description:
MLE and other widely used approximate methods in Mixed Models including Repeated Measures and Grouwth Curves have very serious size (false positive error) problems. Moreover, they also suffer from lack of power problems. The false positive error of MLE based tests concerning randowm effects of mixed models can be as large as 40% when the intened level is only 5%.
Exact statistical methods are especially important in applications involving small samples and/or large variance, which is usually the case in many industrial, pharmaceutical and biomedical research, in particular. Applications of asymptotoc tests and tests which ignore heteroscedasticity can lead to very serious repercussions in such situations.
In this course you will learn how to perform exact procedures, testing of hypotheses and interval estimation that do not suffer from such drawbacks to detect truly significant experimental results in a timely manner.
The participants will also learn how to use tools available from the software specializing in exact parametic methods, XPro.
Instructor:
Dr. Sam Weerahandi
He is the author of the first book specializing in exact statistical Methods, "Exact Statistical Methods for Data Analysis" from Springer-Verlag.
Please visit http://www.dataxiom.com for a complete information.
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