Statistical Strategies for Translational ERP Studies
Statistical Strategies for Translational ERP Studies
This chapter concentrates on the traditional least squares approach to equal means testing in general, and univariate repeated-measures ANOVA as typically applied to event-related potential (ERP) data sets in particular, and suggests that there is an advantage to using a multivariate, unpooled error approach to repeated measures ERP data sets. It reviews two key statistical advances that can enhance the accuracy and power of repeated-measures tests under conditions where the assumption of normality is untenable. The chapter shows that studying the clinical populations typical of translational research places one at increased risk for biased statistical tests when using general linear approaches to equal means testing.
Keywords: ANOVA, event-related potential, normality, least squares, biased statistical tests
MIT Press Scholarship Online requires a subscription or purchase to access the full text of books within the service. Public users can however freely search the site and view the abstracts and keywords for each book and chapter.
Please, subscribe or login to access full text content.
If you think you should have access to this title, please contact your librarian.
To troubleshoot, please check our FAQs, and if you can't find the answer there, please contact us.
