| LC control no. | sh2005008800 |
|---|---|
| LC classification | QA278.3 |
| Topical heading | Structural equation modeling |
| Variant(s) | SEM (Structural equation modeling) |
| See also | Multivariate analysis Factor analysis Regression analysis Path analysis (Statistics) |
| Found in | Work cat.: 2005036850: Structural equation modeling, c2006: CIP galley ("The origins of modern structural equation modeling (SEM) are usually traced to biologist Sewall Wright's development of path analysis. With respect to the social and behavioral sciences, path analysis lay largely dormant until the 1960s when Otis Duncan and others introduced the technique in sociology. Simultaneously, statistical developments by Karl Jöreskog articulated a method for confirmatory factor analysis (CFA), an application of normal theory maximum likelihood estimation to factor models with specific a priori hypothesized theoretical latent structures. [...] Soon after, quite unceremoniously it seems, the fusion of Wright's measured variable path analysis and Jöreskog's CFA occurred and SEM was quietly born.") Sahai, H. Pocket dict. of statistics, 2002 ("The structural equation model refers to a method of analyzing relations between the sets of endogenous and exogenous variables. The procedure consists of the combined application of multiple regression and factor analysis to investigate the relationships between the variables. Equations describing causal relations among the variables are formulated and estimated by the method of maximum likelihood or least squares theory. Most often the endogenous and exogenous variables used in a structural equation model are theoretical constructs or latent variables. The purpose of the analysis is to assess the adequacy of the causal model proposed by the researcher. See also path analysis.") Everitt, B.S. Cambridge dict. of stat., 2002 (structural equation modelling: a procedure that combines aspects of multiple regression and factor analysis to investigate relationships between latent variables) Wikipedia, Dec. 30, 2005 (Structural equation modeling (SEM) is a statistical technique for building and testing models, which are often causal in nature. It is a hybrid technique that encompasses aspects of confirmatory factor analysis, path analysis, and regression.) |
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