Spatially explicit structural equation modeling

Lamb, Eric G., Mengersen, Kerrie L., Stewart, Katherine, Attanayake, Udayanga, & Siciliano, Steven (2014) Spatially explicit structural equation modeling. Ecology, 95(9), pp. 2434-2442.


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Structural equation modeling (SEM) is a powerful statistical approach for the testing of networks of direct and indirect theoretical causal relationships in complex data sets with intercorrelated dependent and independent variables. SEM is commonly applied in ecology, but the spatial information commonly found in ecological data remains difficult to model in a SEM framework. Here we propose a simple method for spatially explicit SEM (SE-SEM) based on the analysis of variance/covariance matrices calculated across a range of lag distances. This method provides readily interpretable plots of the change in path coefficients across scale and can be implemented using any standard SEM software package. We demonstrate the application of this method using three studies examining the relationships between environmental factors, plant community structure, nitrogen fixation, and plant competition. By design, these data sets had a spatial component, but were previously analyzed using standard SEM models. Using these data sets, we demonstrate the application of SE-SEM to regularly spaced, irregularly spaced, and ad hoc spatial sampling designs and discuss the increased inferential capability of this approach compared with standard SEM. We provide an R package, sesem, to easily implement spatial structural equation modeling.

Impact and interest:

7 citations in Scopus
6 citations in Web of Science®
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ID Code: 88787
Item Type: Journal Article
Refereed: Yes
Additional URLs:
Keywords: Lag Distance, Spatial Correlation, Spatial Ecological Analysis, Spatial Environment-Ecological Response Relationships, Structural Equation Modeling, Variance-Covariance Matrices
DOI: 10.1890/13-1997.1
ISSN: 0012-9658
Divisions: Current > Schools > School of Mathematical Sciences
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2014 Ecological Society of America
Deposited On: 28 Oct 2015 03:49
Last Modified: 06 Apr 2017 00:31

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