On the Use of Structural Equation Modeling in Health Communication Research Export

@article{citeulike:5391168, abstract = {Structural equation modeling (SEM) is a multivariate technique suited for testing proposed relations between variables. In this article, the authors discuss the potential for SEM as a tool to advance health communication research both statistically and conceptually. Specifically, the authors discuss the advantages that latent variable modeling in SEM affords researchers by extracting measurement error. In addition, they argue that SEM is useful in understanding communication as a complex set of relations between variables. Moreover, the authors articulate the possibility for examining communication as an agent, mediator, and an outcome. Finally, they review the application of SEM to recursive models, interactions, and confirmatory factor analysis.}, author = {Stephenson, Michael T. and Holbert, R. Lance and Zimmerman, Rick S.}, citeulike-article-id = {5391168}, citeulike-linkout-0 = {http://dx.doi.org/10.1207/s15327027hc2002_7}, doi = {10.1207/s15327027hc2002_7}, journal = {Health Communication}, keywords = {applied, audience, communication, equation, health, modelling, research, review, structural}, number = {2}, pages = {159--167}, posted-at = {2009-08-07 10:50:07}, priority = {2}, publisher = {Routledge}, title = {On the Use of Structural Equation Modeling in Health Communication Research}, url = {http://dx.doi.org/10.1207/s15327027hc2002_7}, volume = {20}, year = {2006} }

TY - JOUR ID - citeulike:5391168 L3 - citeulike-article-id:5391168 N2 - Structural equation modeling (SEM) is a multivariate technique suited for testing proposed relations between variables. In this article, the authors discuss the potential for SEM as a tool to advance health communication research both statistically and conceptually. Specifically, the authors discuss the advantages that latent variable modeling in SEM affords researchers by extracting measurement error. In addition, they argue that SEM is useful in understanding communication as a complex set of relations between variables. Moreover, the authors articulate the possibility for examining communication as an agent, mediator, and an outcome. Finally, they review the application of SEM to recursive models, interactions, and confirmatory factor analysis. IS - 2 JF - Health Communication EP - 167 TI - On the Use of Structural Equation Modeling in Health Communication Research PB - Routledge VL - 20 SP - 159 KW - applied KW - audience KW - communication KW - equation KW - health KW - modelling KW - research KW - review KW - structural AU - Stephenson, Michael AU - Holbert, Lance AU - Zimmerman, Rick PY - 2006/// UR - http://dx.doi.org/10.1207/s15327027hc2002_7 ER -