Abstract
Movement synchrony is studied in various fields of research because the occurrence of movement synchrony correlates with the quality of interaction in terms of liking, rapport, and affiliation. Usually, movement synchrony is investigated with time series and a window-wise computed cross-lagged-correlation. This paper is concerned with the problem that (windowed) cross-lagged-correlation could be confounded by auto-correlation, which may lead to biased conclusions about movement synchrony. The proposed solution combines the idea of a window-wise computed measure and the methodological framework of autoregressive models. As shown through simulated time series, the new method is robust against auto-correlation and identifies the time lag and duration of movement synchrony correctly. At last, the method is applied to real time series of a pilot-study on children’s nonverbal behaviour. Friends vs. non-friends dyads are compared in neutral vs. conflict situations regarding the occurrence of movement synchrony.
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Altmann, U. (2011). Investigation of Movement Synchrony Using Windowed Cross-Lagged Regression. In: Esposito, A., Vinciarelli, A., Vicsi, K., Pelachaud, C., Nijholt, A. (eds) Analysis of Verbal and Nonverbal Communication and Enactment. The Processing Issues. Lecture Notes in Computer Science, vol 6800. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25775-9_31
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DOI: https://doi.org/10.1007/978-3-642-25775-9_31
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