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A guide to robust statistical methods in neuroscience

By Rand R. Wilcox, Guillaume A. Rousselet

Posted 20 Jun 2017
bioRxiv DOI: 10.1101/151811 (published DOI: 10.1002/cpns.41)

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 under- standing of neuroscience 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. The paper 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.

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