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A Copula Approach to Generate Non-Normal Multivariate Data for SEM

Mair, Patrick and Satorra, Albert and Bentler, Peter M. (2011) A Copula Approach to Generate Non-Normal Multivariate Data for SEM. Research Report Series / Department of Statistics and Mathematics, 108. WU Vienna University of Economics and Business, Vienna.

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The present paper develops a procedure based on multivariate copulas for simulating multivariate non-normal data that satisfies a pre-specified covariance matrix. The covariance matrix used, can comply with a specific moment structure form (e.g., a factor analysis or a general SEM model). So the method is particularly useful for Monte Carlo evaluation of SEM models in the context of non-normal data. The new procedure for non-normal data simulation is theoretically described and also implemented on the widely used R environment. The quality of the method is assessed by performing Monte Carlo simulations. Within this context a one-sample test on the observed VC-matrix is involved. This test is robust against normality violations. This test is defined through a particular SEM setting. Finally, an example for Monte Carlo evaluation of SEM modeling of non-normal data using this method is presented. (author's abstract)

Item Type: Paper
Keywords: Multivariate Copulas / Structural Equation Modeling (SEM) / Robust One-Sample Test Covariance Matrix / Monte Carlo Simulations / Non-Normal Data SEM
Divisions: Departments > Finance, Accounting and Statistics > Statistics and Mathematics
Depositing User: Josef Leydold
Date Deposited: 15 Jun 2011 09:29
Last Modified: 11 Oct 2014 13:13
URI: http://epub.wu.ac.at/id/eprint/3122


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