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Structural Equation Modeling

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Statistical Human Genetics

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1666))

Abstract

Structural equation modeling (SEM) is a multivariate statistical framework that is used to model complex relationships between directly observed and indirectly observed (latent) variables. SEM is a general framework that involves simultaneously solving systems of linear equations and encompasses other techniques such as regression, factor analysis, path analysis, and latent growth curve modeling. Recently, SEM has gained popularity in the analysis of complex genetic traits because it can be used to better analyze the relationships between correlated variables (traits), to model genes as latent variables as a function of multiple observed genetic variants, and to assess the association between multiple genetic variants and multiple correlated phenotypes of interest. Though the general SEM framework only allows for the analysis of independent observations, recent work has extended SEM for the analysis of data on general pedigrees. Here, we review the theory of SEM for both unrelated and family data, describe the available software for SEM, and provide examples of SEM analysis.

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Author information

Authors and Affiliations

  1. Department of Population and Quantitative Health Sciences, Case Western Reserve University School of Medicine, Wolstein Research Building, 2103 Cornell Road, Cleveland, OH, 44106-7281, USA

    Catherine M. Stein, Nathan J. Morris, Noémi B. Hall & Nora L. Nock

  2. Center for Proteomics and Bioinformatics, Case Western Reserve University, Cleveland, OH, USA

    Catherine M. Stein

Authors
  1. Catherine M. Stein
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  2. Nathan J. Morris
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  3. Noémi B. Hall
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  4. Nora L. Nock
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Corresponding author

Correspondence to Catherine M. Stein .

Editor information

Editors and Affiliations

  1. Case Western Reserve University, Cleveland, OH, USA

    Robert C. Elston

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© 2017 Springer Science+Business Media LLC

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Stein, C.M., Morris, N.J., Hall, N.B., Nock, N.L. (2017). Structural Equation Modeling. In: Elston, R. (eds) Statistical Human Genetics. Methods in Molecular Biology, vol 1666. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7274-6_28

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  • DOI: https://doi.org/10.1007/978-1-4939-7274-6_28

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7273-9

  • Online ISBN: 978-1-4939-7274-6

  • eBook Packages: Springer Protocols

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