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Residual-based diagnostics for structural equation models
Journal article   Open access   Peer reviewed

Residual-based diagnostics for structural equation models

B N Sánchez, E A Houseman and L M Ryan
Biometrics, v 65(1), pp 104-115
Mar 2009
DOI: https://doi.org/10.1111/j.1541-0420.2008.01022.x
PMID: 18373712
Featured in Collection :   UN Sustainable Development Goals @ Drexel
url
http://hdl.handle.net/2027.42/65983View
SubmittedOpen Access (License Unspecified),  Open

Abstract

Models, Theoretical Pregnancy Data Interpretation, Statistical Computer Simulation Humans Lead Female Biometry - methods Maternal Exposure
Classical diagnostics for structural equation models are based on aggregate forms of the data and are ill suited for checking distributional or linearity assumptions. We extend recently developed goodness-of-fit tests for correlated data based on subject-specific residuals to structural equation models with latent variables. The proposed tests lend themselves to graphical displays and are designed to detect misspecified distributional or linearity assumptions. To complement graphical displays, test statistics are defined; the null distributions of the test statistics are approximated using computationally efficient simulation techniques. The properties of the proposed tests are examined via simulation studies. We illustrate the methods using data from a study of in utero lead exposure.

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13 citations in Web of Science
14 citations in Scopus

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Collaboration types
Domestic collaboration
Web of Science research areas
Biology
Mathematical & Computational Biology
Statistics & Probability
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