Neuroimaging dead salmon…

"It is a recognized problem in statistics that as additional hypothesis tests are conducted on a set of data there is a parallel increase in the familywise error rate (FWER). 

"This represents the probability of making one or more false discoveries, also known as type I errors. 

"At an original significance threshold of p = 0.001 the probability of a falsely significant result is represented by the formula 1-0.999n, where n represents the number of tests conducted. By 52 tests the probability of a false result has increased to p = 0.051. 

"With 130,000 voxels the probability of a false discovery approaches p = 1.0. The Bonferroni correction is perhaps the most famous approach to the multiple comparisons problem, but is not the only strategy to address this issue. 

"The aim of this project was to demonstrate the necessity of multiple comparisons correction in functional neuroimaging and to highlight some easy methods of correction built in to popular software." 




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