title: Application of structural equation modeling to health outcomes research.
abstract: This article provides an overview of the basic underlying principles of structural equation modeling (SEM). SEM models have two basic elements: a measurement model and a structural model. The measurement model describes the associations between the indicators (observed measures) of the latent variables, whereas the structural model delineates the direct and indirect substantive effects among latent variables and between measured and latent variables. The application of SEM to health outcomes research is illustrated using two examples: (a) assessing the equivalence of the SF-36 and patient evaluations of care for English- and Spanish-language respondents and (b) evaluating a theoretical model of health in myocardial infarction patients. The results of SEM studies can contribute to better understanding of the validity of health outcome measures and of relationships between physiologic, clinical, and health outcome variables.
authors.affiliation: University of California, Los Angeles, USA. drhays@ucla.edu
authors.forename: Ron D
authors.initials: RD
authors.lastname: Hays
authors.forename: Dennis
authors.initials: D
authors.lastname: Revicki
authors.forename: Karin S
authors.initials: KS
authors.lastname: Coyne
mesh_terms: D003431:Cross-Cultural Comparison; D005163:Factor Analysis, Statistical; D006305:Health Status Indicators; D006801:Humans; D017059:Models, Econometric; D008962:Models, Theoretical; D009203:Myocardial Infarction / Q000628:therapy; D017063:Outcome Assessment, Health Care / Q000379:methods*; D011594:Psychometrics; D012984:Software; D011795:Surveys and Questionnaires; D014177:Translations