Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/99662
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dc.contributorDepartment of Management and Marketingen_US
dc.creatorWong, MNen_US
dc.creatorKenny, DAen_US
dc.creatorKnight, APen_US
dc.date.accessioned2023-07-18T03:13:11Z-
dc.date.available2023-07-18T03:13:11Z-
dc.identifier.issn1094-4281en_US
dc.identifier.urihttp://hdl.handle.net/10397/99662-
dc.language.isoenen_US
dc.publisherSAGE Publicationsen_US
dc.rightsThis is the accepted version of the publication Wong, M.-N., Kenny, D. A., & Knight, A. P. (2024). SRM_R: A Web-Based Shiny App for Social Relations Analyses. Organizational Research Methods, 27(1), 114-139. Copyright © 2022 (The Author(s)). DOI: 10.1177/10944281221134104.en_US
dc.subjectDirected dyadic dataen_US
dc.subjectShinyen_US
dc.subjectSocial relations designsen_US
dc.subjectSocial relations modelen_US
dc.titleSRM_R : a web-based shiny app for social relations analysesen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage114en_US
dc.identifier.epage139en_US
dc.identifier.volume27en_US
dc.identifier.issue1en_US
dc.identifier.doi10.1177/10944281221134104en_US
dcterms.abstractMany topics in organizational research involve examining the interpersonal perceptions and behaviors of group members. The resulting data can be analyzed using the social relations model (SRM). This model enables researchers to address several important questions regarding relational phenomena. In the model, variance can be partitioned into group, actor, partner, and relationship; reciprocity can be assessed in terms of individuals and dyads; and predictors at each of these levels can be analyzed. However, analyzing data using the currently available SRM software can be challenging and can deter organizational researchers from using the model. In this article, we provide a “go-to” introduction to SRM analyses and propose SRM_R (https://davidakenny.shinyapps.io/SRM_R/), an accessible and user-friendly, web-based application for SRM analyses. The basic steps of conducting SRM analyses in the app are illustrated with a sample dataset of 47 teams, 228 members, and 884 dyadic observations, using the participants’ ratings of the advice-seeking behavior of their fellow employees.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationOrganizational research methods, Jan. 2024, v. 27, no. 1, p. 114-139en_US
dcterms.isPartOfOrganizational research methodsen_US
dcterms.issued2024-01-
dc.identifier.scopus2-s2.0-85142694578-
dc.identifier.eissn1552-7425en_US
dc.description.validate202307 bckwen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumbera2266 [Non PolyU]-
dc.identifier.SubFormID47270-
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryGreen (AAM)en_US
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