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In the present paper we propose a non-parametric statistical test procedure for interval scaled, paired samples data that circumvents the multiple comparison problem (MCP) by relating the data to the rank order of its group averages. Using an auto-regressive procedure, a single test statistic for multiple groups is obtained that allows for qualitative statements about whether multiple group averages are in fact different and how they can be sorted. The presented procedure outperforms classical tests, such as pairwise conducted t-tests and ANOVA, in some circumstances. Furthermore, the test is robust against noise and does not require the data to follow any particular distribution. If A is a data matrix containing N observations for k groups, then the test statistic η can be computed by , where s is a vector of length k containing the average for each group, transformed into unique rank values. This statistic is compared to the distribution D, obtained by Monte Carlo sampling from the permutation distribution. It will be demonstrated that D can be described by a normal distribution for a variety of input data distributions and choices for f, as long as a set of criteria is met. Comparing η to the permutation distribution controls the false alarm (FA) rate sufficiently, since the exact p-value can be estimated [1]. Multiple examples of possible choices for f will be discussed, as well as detailed descriptions of the underlying test assumptions, possible interpretations and use cases. All mathematical derivations are supported with a set of simulations, written in Python that can be downloaded from https://gitlab.com/TommyClausner/aros-test together with an implementation of the test itself.

You have access Check for updates on crossmark Research articles Enhanced self-reported affect and prosocial behaviour without differential physiological responses in mirror-sensory synaesthesia Kalliopi Ioumpa, Sarah A. Graham, Tommy Clausner, Simon E. Fisher, Rob van Lier and Tessa M. van Leeuwen Published:21 October 2019https://doi.org/10.1098/rstb.2019.0395 Abstract Mirror-sensory synaesthetes mirror the pain or touch that they observe in other people on their own bodies. This type of synaesthesia has been associated with enhanced empathy. We investigated whether the enhanced empathy of people with mirror-sensory synesthesia influences the experience of situations involving touch or pain and whether it affects their prosocial decision making. Mirror-sensory synaesthetes (N = 18, all female), verified with a touch-interference paradigm, were compared with a similar number of age-matched control individuals (all female). Participants viewed arousing images depicting pain or touch; we recorded subjective valence and arousal ratings, and physiological responses, hypothesizing more extreme reactions in synaesthetes. The subjective impact of positive and negative images was stronger in synaesthetes than in control participants; the stronger the reported synaesthesia, the more extreme the picture ratings. However, there was no evidence for differential physiological or hormonal responses to arousing pictures. Prosocial decision making was assessed with an economic game assessing altruism, in which participants had to divide money between themselves and a second player. Mirror-sensory synaesthetes donated more money than non-synaesthetes, showing enhanced prosocial behaviour, and also scored higher on the Interpersonal Reactivity Index as a measure of empathy. Our study demonstrates the subjective impact of mirror-sensory synaesthesia and its stimulating influence on prosocial behaviour. This article is part of the discussion meeting issue ‘Bridging senses: novel insights from synaesthesia’.