David Bourget (Western Ontario)
David Chalmers (ANU, NYU)
Rafael De Clercq
Jack Alan Reynolds
Learn more about PhilPapers
Linear structural equation models (SEMs) are widely used in sociology, econometrics, biology, and other sciences. A SEM (without free parameters) has two parts: a probability distribution (in the Normal case specified by a set of linear structural equations and a covariance matrix among the “error” or “disturbance” terms), and an associated path diagram corresponding to the functional composition of variables specified by the structural equations and the correlations among the error terms. It is often thought that the path diagram is nothing more than a heuristic device for illustrating the assumptions of the model. However, in this paper, we will show how path diagrams can be used to solve a number of important problems in structural equation modelling.
|Keywords||No keywords specified (fix it)|
No categories specified
(categorize this paper)
|Through your library||Only published papers are available at libraries|
Similar books and articles
Robert Audi (1991). Structural Justification. Journal of Philosophical Research 16:473-492.
James R. Griesemer (1991). Must Scientific Diagrams Be Eliminable? The Case of Path Analysis. Biology and Philosophy 6 (2):155-180.
Damien Fennell (2007). Why Functional Form Matters: Revealing the Structure in Structural Models in Econometrics. Philosophy of Science 74 (5):1033-1045.
Philip T. Smith, Frank McKenna, Claire Pattison & Andrea Waylen (2001). Structural Equation Modelling of Human Judgement. Thinking and Reasoning 7 (1):51 – 68.
Thomas Richardron, Fast Recalculation of the Covariance Matrix Implied by a Recursive Structural Equation Model.
W. M. Goodwin (2008). Structural Formulas and Explanation in Organic Chemistry. Foundations of Chemistry 10 (2):117-127.
Added to index2009-01-28
Total downloads13 ( #98,746 of 1,004,638 )
Recent downloads (6 months)1 ( #64,617 of 1,004,638 )
How can I increase my downloads?