Action Effects on Visual Perception of Distances: A Multilevel Bayesian Meta-Analysis

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Description: Some studies suggested that action constraints influence visual perception of distances. For instance, the greater the effort to cover a distance, the longer people perceive this distance. The present multilevel Bayesian meta-analysis supports the existence of a small action constraint effect on distance estimation, Hedge’s g = 0.29, 95% CrI [0.16, 0.47] (Nstudies = 37, Nparticipants = 1035). This effect slightly varied according to the action constraint category (i.e., effort, weight, and tool-use) but not according to participants’ motor intention. Some authors argued such effects reflect experimental demand biases rather than genuine perceptual effects. Our meta-analysis did not allow to dismiss this possibility, but it did not support it. We provide field-specific conventions for interpreting action constraint effect sizes and minimum sample size to detect them with 90% power. We encourage researchers to improve this meta-analysis using our online repository (https://osf.io/bc3wn/wiki/home/) to send their published or unpublished data. **Please, read the README and the associated FAQ to know how to send the data.**

License: CC0 1.0 Universal

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README Welcome to our OSF project aimed at promoting our continuous multilevel Bayesian meta-analysis of the effect of physical action constraints on visual perception of distance. This repository contains the pre-print of our manuscript, which is already submitted to a peer-reviewed journal, as well as the Supplementary Materials, the full R code used to conduct our analyses, a .xls file listing ...

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