Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/99662
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Management and Marketing | en_US |
| dc.creator | Wong, MN | en_US |
| dc.creator | Kenny, DA | en_US |
| dc.creator | Knight, AP | en_US |
| dc.date.accessioned | 2023-07-18T03:13:11Z | - |
| dc.date.available | 2023-07-18T03:13:11Z | - |
| dc.identifier.issn | 1094-4281 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/99662 | - |
| dc.language.iso | en | en_US |
| dc.publisher | SAGE Publications | en_US |
| dc.rights | This 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.subject | Directed dyadic data | en_US |
| dc.subject | Shiny | en_US |
| dc.subject | Social relations designs | en_US |
| dc.subject | Social relations model | en_US |
| dc.title | SRM_R : a web-based shiny app for social relations analyses | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.spage | 114 | en_US |
| dc.identifier.epage | 139 | en_US |
| dc.identifier.volume | 27 | en_US |
| dc.identifier.issue | 1 | en_US |
| dc.identifier.doi | 10.1177/10944281221134104 | en_US |
| dcterms.abstract | Many 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.accessRights | open access | en_US |
| dcterms.bibliographicCitation | Organizational research methods, Jan. 2024, v. 27, no. 1, p. 114-139 | en_US |
| dcterms.isPartOf | Organizational research methods | en_US |
| dcterms.issued | 2024-01 | - |
| dc.identifier.scopus | 2-s2.0-85142694578 | - |
| dc.identifier.eissn | 1552-7425 | en_US |
| dc.description.validate | 202307 bckw | en_US |
| dc.description.oa | Accepted Manuscript | en_US |
| dc.identifier.FolderNumber | a2266 [Non PolyU] | - |
| dc.identifier.SubFormID | 47270 | - |
| dc.description.fundingSource | Self-funded | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.description.oaCategory | Green (AAM) | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Wong_Web-Based_Shiny_App.pdf | Pre-Published version | 2.65 MB | Adobe PDF | View/Open |
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