City Research Online

A note on detecting statistical outliers in psychophysical data

Jones, P. R. ORCID: 0000-0001-7672-8397 (2019). A note on detecting statistical outliers in psychophysical data. Attention, Perception, and Psychophysics, 81(5), pp. 1189-1196. doi: 10.3758/s13414-019-01726-3

Abstract

This paper considers how to identify statistical outliers in psychophysical datasets, where the underlying sampling distributions are unknown. Eight methods are described, and each is evaluated using Monte Carlo simulations of a typical psychophysical experiment. The best method is shown to be one based on a measure of spread known as S n . This is shown to be more sensitive than popular heuristics based on standard deviations from the mean, and more robust than non-parametric methods based on percentiles or interquartile range. MATLAB code for computing S n is included.

Publication Type: Article
Additional Information: © The Author(s) 2019. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Subjects: H Social Sciences > HA Statistics
R Medicine > RE Ophthalmology
Departments: School of Health Sciences > Optometry & Visual Science
URI: https://openaccess.city.ac.uk/id/eprint/21552
[img]
Preview
Text - Published Version
Available under License Creative Commons Attribution.

Download (3MB) | Preview

Export

Downloads

Downloads per month over past year

View more statistics

Actions (login required)

Admin Login Admin Login