Lagged Multidimensional Recurrence Quantification Analysis for Determining Leader–Follower Relationships Within Multidimensional Time Series

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

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Lagged Multidimensional Recurrence Quantification Analysis for Determining Leader–Follower Relationships Within Multidimensional Time Series. / Tomashin, Alon; Gordon, Ilanit; Leonardi, Giuseppe et al.
in: Psychological Methods, 10.10.2024.

Publikation: Beiträge in ZeitschriftenZeitschriftenaufsätzeForschungbegutachtet

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Tomashin A, Gordon I, Leonardi G, Berson Y, Milstein N, Ziegler M et al. Lagged Multidimensional Recurrence Quantification Analysis for Determining Leader–Follower Relationships Within Multidimensional Time Series. Psychological Methods. 2024 Okt 10. Epub 2024 Okt 10. doi: 10.1037/met0000691

Bibtex

@article{1baa7c9211ea40a2bbae1573381d5fa6,
title = "Lagged Multidimensional Recurrence Quantification Analysis for Determining Leader–Follower Relationships Within Multidimensional Time Series",
abstract = "The current article introduces lagged multidimensional recurrence quantification analysis. The method is an extension of multidimensional recurrence quantification analysis and allows to quantify the joint dynamics of multivariate time series and to investigate leader–follower relationships in behavioral and physiological data. Moreover, the method enables the quantification of the joint dynamics of a group, when such leader–follower relationships are taken into account. We first provide a formal presentation of the method, and then apply it to synthetic data, as well as data sets from joint action research, investigating the shared dynamics of facial expression and beats-per-minute recordings within different groups. A wrapper function is included, for applying the method together with the “crqa” package in R.",
keywords = "joint action, leader–follower dynamics, multidimensional recurrence quantification analysis, multivariate time series, Psychology",
author = "Alon Tomashin and Ilanit Gordon and Giuseppe Leonardi and Yair Berson and Nir Milstein and Matthias Ziegler and Ursula Hess and Sebastian Wallot",
note = "Publisher Copyright: {\textcopyright} 2024 The Author(s)",
year = "2024",
month = oct,
day = "10",
doi = "10.1037/met0000691",
language = "English",
journal = "Psychological Methods",
issn = "1082-989X",
publisher = "American Psychological Association Inc.",

}

RIS

TY - JOUR

T1 - Lagged Multidimensional Recurrence Quantification Analysis for Determining Leader–Follower Relationships Within Multidimensional Time Series

AU - Tomashin, Alon

AU - Gordon, Ilanit

AU - Leonardi, Giuseppe

AU - Berson, Yair

AU - Milstein, Nir

AU - Ziegler, Matthias

AU - Hess, Ursula

AU - Wallot, Sebastian

N1 - Publisher Copyright: © 2024 The Author(s)

PY - 2024/10/10

Y1 - 2024/10/10

N2 - The current article introduces lagged multidimensional recurrence quantification analysis. The method is an extension of multidimensional recurrence quantification analysis and allows to quantify the joint dynamics of multivariate time series and to investigate leader–follower relationships in behavioral and physiological data. Moreover, the method enables the quantification of the joint dynamics of a group, when such leader–follower relationships are taken into account. We first provide a formal presentation of the method, and then apply it to synthetic data, as well as data sets from joint action research, investigating the shared dynamics of facial expression and beats-per-minute recordings within different groups. A wrapper function is included, for applying the method together with the “crqa” package in R.

AB - The current article introduces lagged multidimensional recurrence quantification analysis. The method is an extension of multidimensional recurrence quantification analysis and allows to quantify the joint dynamics of multivariate time series and to investigate leader–follower relationships in behavioral and physiological data. Moreover, the method enables the quantification of the joint dynamics of a group, when such leader–follower relationships are taken into account. We first provide a formal presentation of the method, and then apply it to synthetic data, as well as data sets from joint action research, investigating the shared dynamics of facial expression and beats-per-minute recordings within different groups. A wrapper function is included, for applying the method together with the “crqa” package in R.

KW - joint action

KW - leader–follower dynamics

KW - multidimensional recurrence quantification analysis

KW - multivariate time series

KW - Psychology

UR - http://www.scopus.com/inward/record.url?scp=85206660437&partnerID=8YFLogxK

U2 - 10.1037/met0000691

DO - 10.1037/met0000691

M3 - Journal articles

C2 - 39388104

AN - SCOPUS:85206660437

JO - Psychological Methods

JF - Psychological Methods

SN - 1082-989X

ER -

DOI