A Guide to Robust Statistical Methods in Neuroscience. Issue 1 (22nd January 2018)

• Record Type: Journal Article
• Authors: Wilcox, Rand R.; Rousselet, Guillaume A.
• Editors: Gerfen, Charles R.; Holmes, Andrew; Sibley, David; Skolnick, Phil; Wray, Susan
• Is Part Of: Current protocols in neuroscience. Issue 82:Issue 1(2018)
• Page Start: 8.42.1
• Page End: 8.42.30
• Publication Date: 2018-01-22
• Subjects: non‐normality -- heteroscedasticity -- skewed distributions -- outliers -- curvature; Neurosciences -- Laboratory manuals; Neurosciences; Cytological Techniques; Histological Techniques; Nervous System -- anatomy & histology; Neurosciences; Laboratory Manual; Laboratory manuals; 612.8
• DOI: 10.1002/cpns.41
• Languages: English
• ISSNs: 1934-8576

Abstract

Abstract: There is a vast array of new and improved methods for comparing groups and studying associations that offer the potential for substantially increasing power, providing improved control over the probability of a Type I error, and yielding a deeper and more nuanced understanding of data. These new techniques effectively deal with four insights into when and why conventional methods can be unsatisfactory. But for the non‐statistician, the vast array of new and improved techniques for comparing groups and studying associations can seem daunting, simply because there are so many new methods that are now available. This unit briefly reviews when and why conventional methods can have relatively low power and yield misleading results. The main goal is to suggest some general guidelines regarding when, how, and why certain modern techniques might be used. © 2018 by John Wiley & Sons, Inc.