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      Body sway predicts romantic interest in speed dating

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          Abstract

          Social bonding is fundamental to human society, and romantic interest involves an important type of bonding. Speed dating research paradigms offer both high external validity and experimental control for studying romantic interest in real-world settings. While previous studies focused on the effect of social and personality factors on romantic interest, the role of non-verbal interaction has been little studied in initial romantic interest, despite being commonly viewed as a crucial factor. The present study investigated whether romantic interest can be predicted by non-verbal dyadic interactive body sway, and enhanced by movement-promoting (‘groovy’) background music. Participants’ body sway trajectories were recorded during speed dating. Directional (predictive) body sway coupling, but not body sway similarity, predicted interest in a long-term relationship above and beyond rated physical attractiveness. In addition, presence of groovy background music promoted interest in meeting a dating partner again. Overall, we demonstrate that romantic interest is reflected by non-verbal body sway in dyads in a real-world dating setting. This novel approach could potentially be applied to investigate non-verbal aspects of social bonding in other dynamic interpersonal interactions such as between infants and parents and in non-verbal populations including those with communication disorders.

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          Most cited references36

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          Fitting Linear Mixed-Effects Models Using lme4

          Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in an lmer call by a formula, in this case including both fixed- and random-effects terms. The formula and data together determine a numerical representation of the model from which the profiled deviance or the profiled REML criterion can be evaluated as a function of some of the model parameters. The appropriate criterion is optimized, using one of the constrained optimization functions in R, to provide the parameter estimates. We describe the structure of the model, the steps in evaluating the profiled deviance or REML criterion, and the structure of classes or types that represents such a model. Sufficient detail is included to allow specialization of these structures by users who wish to write functions to fit specialized linear mixed models, such as models incorporating pedigrees or smoothing splines, that are not easily expressible in the formula language used by lmer. Journal of Statistical Software, 67 (1) ISSN:1548-7660
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            Likert scales, levels of measurement and the "laws" of statistics.

            Reviewers of research reports frequently criticize the choice of statistical methods. While some of these criticisms are well-founded, frequently the use of various parametric methods such as analysis of variance, regression, correlation are faulted because: (a) the sample size is too small, (b) the data may not be normally distributed, or (c) The data are from Likert scales, which are ordinal, so parametric statistics cannot be used. In this paper, I dissect these arguments, and show that many studies, dating back to the 1930s consistently show that parametric statistics are robust with respect to violations of these assumptions. Hence, challenges like those above are unfounded, and parametric methods can be utilized without concern for "getting the wrong answer".
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              Analyzing and interpreting data from likert-type scales.

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                Author and article information

                Contributors
                Journal
                Soc Cogn Affect Neurosci
                Soc Cogn Affect Neurosci
                scan
                Social Cognitive and Affective Neuroscience
                Oxford University Press (UK )
                1749-5016
                1749-5024
                18 July 2020
                Jan-Feb 2021
                18 July 2020
                : 16
                : 1-2 , Interpersonal Synchrony Special Issue
                : 185-192
                Affiliations
                Department of Psychology , Neuroscience and Behaviour, McMaster University , Hamilton L8S 4K1, Canada
                Department of Psychology , Neuroscience and Behaviour, McMaster University , Hamilton L8S 4K1, Canada
                Department of Psychology , Neuroscience and Behaviour, McMaster University , Hamilton L8S 4K1, Canada
                Department of Psychology , Neuroscience and Behaviour, McMaster University , Hamilton L8S 4K1, Canada
                McMaster Institute for Music and the Mind , McMaster University , Hamilton L8S 4K1, Canada
                Department of Psychology , Neuroscience and Behaviour, McMaster University , Hamilton L8S 4K1, Canada
                Cognitive Brain Research Unit , Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki , Helsinki 00014, Finland
                Department of Psychology , Neuroscience and Behaviour, McMaster University , Hamilton L8S 4K1, Canada
                McMaster Institute for Music and the Mind , McMaster University , Hamilton L8S 4K1, Canada
                Rotman Research Institute , Baycrest Hospital , Toronto M6A 2E1, Canada
                Author notes
                Correspondence should be addressed to Laurel J. Trainor, Department of Psychology, Neuroscience and Behaviour, McMaster University, 1280 Main St W, Hamilton L8S 4L8, Canada. E-mail: ljt@ 123456mcmaster.ca
                Author information
                http://orcid.org/0000-0001-6745-4435
                http://orcid.org/0000-0003-3137-7655
                Article
                nsaa093
                10.1093/scan/nsaa093
                7812630
                32685965
                ac9e2638-9839-4716-9d52-1821d86ea6f9
                © The Author(s) 2020. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 17 January 2020
                : 12 June 2020
                : 24 June 2020
                Page count
                Pages: 8
                Funding
                Funded by: Social Sciences and Humanities Research Council of Canada, DOI 10.13039/501100000155;
                Award ID: 435-2016-1442
                Funded by: Natural Sciences and Engineering Research Council of Canada, DOI 10.13039/501100000038;
                Award ID: RGPIN-2014-0470
                Funded by: Canadian Institutes of Health Research, DOI 10.13039/501100000024;
                Award ID: MOP 153130
                Funded by: Canadian Institute for Advanced Research, DOI 10.13039/100007631;
                Categories
                Original Manuscript
                AcademicSubjects/SCI01880

                Neurosciences
                interpersonal interaction,romantic interest,groove,granger causality,mixed effect model

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