False Positives and Other Statistical Errors in Standard Analyses of Eye Movements in Reading.

ABSTRACT: In research on eye movements in reading, it is common to analyze a number of canonical dependent measures to study how the effects of a manipulation unfold over time. Although this gives rise to the well-known multiple comparisons problem, i.e. an inflated probability that the null hypothesis is incorrectly rejected (Type I error), it is accepted standard practice not to apply any correction procedures. Instead, there appears to be a widespread belief that corrections are not necessary because the increase in false positives is too small to matter. To our knowledge, no formal argument has ever been presented to justify this assumption. Here, we report a computational investigation of this issue using Monte Carlo simulations. Our results show that, contrary to conventional wisdom, false pos

SUBMITTER: von der Malsburg T 

PROVIDER: S-EPMC5461930 | biostudies-literature | 2017 Jun

REPOSITORIES: biostudies-literature