Abstract
In analyzing a linear model we can examine as many single degree of freedom hypotheses as we want. If we test all of these hypotheses at, say, the .05 level, then the (weak) experimentwise error rate (the probability of rejecting at least one of these hypotheses when all are true) will be greater than .05. Multiple comparison techniques are methods of performing the tests so that if all the hypotheses are true, then the probability of rejecting any of the hypotheses is no greater than some specified value, i.e., the experimentwise error rate is controlled.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 1996 Springer Science+Business Media New York
About this chapter
Cite this chapter
Christensen, R. (1996). Multiple Comparison Techniques. In: Plane Answers to Complex Questions. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-2477-6_5
Download citation
DOI: https://doi.org/10.1007/978-1-4757-2477-6_5
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4757-2479-0
Online ISBN: 978-1-4757-2477-6
eBook Packages: Springer Book Archive