kleinbub/rMEA: Synchrony in Motion Energy Analysis (MEA) Time-Series
A suite of tools useful to read, visualize and export bivariate motion energy time-series. Lagged synchrony between subjects can be analyzed through windowed cross-correlation. Surrogate data generation allows an estimation of pseudosynchrony that helps to estimate the effect size of the observed synchronization. Kleinbub, J. R., & Ramseyer, F. T. (2020). rMEA: An R package to assess nonverbal synchronization in motion energy analysis time-series. Psychotherapy research, 1-14. <doi:10.1080/10503307.2020.1844334>.
Getting started
Browse package contents
Package details |
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| Author | Johann R. Kleinbub, Fabian Ramseyer |
| Maintainer | Johann R. Kleinbub <johann.kleinbub@gmail.com> |
| License | GPL-3 |
| Version | 1.3.0 |
| URL | https://github.com/kleinbub/rMEA https://psync.ch |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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