Introduction to Multiple Comparison Procedures
Sunday morning, July, 8
Jason C. Hsu, The Ohio State University
This course will use real applications to illustrate concepts and
techniques in multiple comparisons. Error rate concepts covered include
Familywise Error Rate, False Discovery Rate, and generalized Familywise
Error Rate. Multiple test construction techniques covered include union
intersection testing, intersection union testing, closed testing, and
partition testing. Conditions for shortcutting closed/partition tests to
step-up and step-down tests, and validity of re-sampling methods, will be
given. Applications covered include equivalence testing, dose-response
studies, and analysis of gene expressions from microarray experiments.
Outline:
- Concepts of error rates
- Principles of multiple test construction
- Equivalence inference
- Dose-response studies
- Pharmacogenomicss
Bio sketch:
Jason Hsu teaches at the Ohio State University. He and his students have
been involved in developing a principle now called the Partitioning
Principle which has given useful insights into stepwise testing and
confidence set construction. He has worked on implementing multiple
comparison methods in statistical packages, and pharmaceutical statistics
problems such as bioequivalence and dose-response. His current research
includes statistical design and analysis of microarray experiments,
control of the generalized Familywise error rate, and model assumption
required for validity of re-sampling methods such as permutation tests.
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