dc.contributor.authorRosenthal, Sonny
dc.identifier.citationRosenthal, S. (2013). Measuring differentials in communication research : issues with multicollinearity in three methods. Communication methods and measures, 7(2), 106-125.en_US
dc.description.abstractModels of communication processes sometimes require the computation of the difference between two variables. For example, information insufficiency is the difference between what people know and what they think they need to know about an issue, and it can motivate information seeking and processing. Common methods that compute this differential may bias model estimates as a function of the correlation between the differentiated variables and other variables in the model. This article describes Cohen and Cohen’s (1983) analysis of partial variance for computing differentials, and analyzes simulated data in order to contrast that method with two alternative methods. The discussion recommends the use of the Cohen and Cohen method in other areas of communication research, such as studies of third-person perception.en_US
dc.format.extent39 pages.en_US
dc.relation.ispartofseriesCommunication methods and measuresen_US
dc.rights© 2013 Taylor & Francis Group, LLC. This is the author created version of a work that has been peer reviewed and accepted for publication by Communication Methods and Measures, Taylor & Francis Group, LLC. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [DOI: http://dx.doi.org/10.1080/19312458.2013.789837].en_US
dc.subjectDRNTU::Social sciences::Communication::Communication theories and models
dc.titleMeasuring differentials in communication research : issues with multicollinearity in three methodsen_US
dc.typeJournal Article
dc.contributor.schoolWee Kim Wee School of Communication and Informationen_US
dc.description.versionAccepted versionen_US

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