Statistical analyses
All statistical tests were two-tailed with an alpha of 0.05 to determine
statistical significance. Non-parametric tests were used for
non-normally distributed data. Holm-Bonferroni corrections were used for
post-hoc pairwise comparisons.
A linear mixed effects model (LME) was used to examine differences in
pupil responses after tactile stimulation of the different body parts
and the control condition. The best model was determined by using the
Bayesian Information Criterion (BIC), with pupil size derivative as the
dependent variable, using random intercepts for each participant.
Stimulation site was used as an independent variable (i.e., control
condition, little finger, forearm, and calf). The trial number within a
block and the block number were additionally included to control for
possible habituation effects. It is recommended to fit random slopes for
predictor variables unless this leads to non-convergence of the model.
As this was the case for several time points, we followed Barr (2013)
and only fitted random intercepts.
Next, we tested whether potential differences in the pupil size
derivative could be explained by differences in the response latency.
The time to the maximum pupil size derivative between the three
stimulation sites was compared using Friedman’s ANOVA.
To assess whether the three body locations differed in terms of tactile
sensitivity, the Von Frey tactile sensitivity threshold was compared
between body locations using Friedman’s ANOVA.
Data availability
All raw data, materials, analysis scripts, as well as the
preregistration can be retrieved via the open Science Framework:
https://osf.io/rb3gh/?view_only=2859615bba494f3393b54315fe5aa797.