Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/45432
Title: Robust regression estimates in the prediction of latent variables in structural equation models
Keywords: Accuracy
Monte Carlo simulation
Normal asymmetry
Precision
Métodos de regressão
Modelagem de equações estruturais
Simulação de Monte Carlo
Issue Date: May-2012
Publisher: Wayne State University
Citation: CIRILLO, M. A.; BARROSO, L. P. Robust regression estimates in the prediction of latent variables in structural equation models. Journal of Modern Applied Statistical Methods, [S.l.], v. 11, n. 1, p. 42-53, May 2012. DOI: 10.22237/jmasm/1335844980.
Abstract: The incorporation of the robust regression methods Least Median Square (LMS) and Least Trimmed Squares (LTS) is proposed in structural equation modeling. Results show that, in situations of high deviations of symmetry, the evaluated methods would be recommended for applications including smaller sample sizes.
URI: https://digitalcommons.wayne.edu/jmasm/vol11/iss1/4/
http://repositorio.ufla.br/jspui/handle/1/45432
Appears in Collections:DES - Artigos publicados em periódicos

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