Applications of structural equation modeling (SEM) in ecological studies: an updated review
TLDR
The essential components and variants of structural equation modeling (SEM) are introduced, the common issues in SEM applications are synthesized, and the views on SEM’s future in ecological research are shared.Abstract:
This review was developed to introduce the essential components and variants of structural equation modeling (SEM), synthesize the common issues in SEM applications, and share our views on SEM’s future in ecological research. We searched the Web of Science on SEM applications in ecological studies from 1999 through 2016 and summarized the potential of SEMs, with a special focus on unexplored uses in ecology. We also analyzed and discussed the common issues with SEM applications in previous publications and presented our view for its future applications. We searched and found 146 relevant publications on SEM applications in ecological studies. We found that five SEM variants had not commenly been applied in ecology, including the latent growth curve model, Bayesian SEM, partial least square SEM, hierarchical SEM, and variable/model selection. We identified ten common issues in SEM applications including strength of causal assumption, specification of feedback loops, selection of models and variables, identification of models, methods of estimation, explanation of latent variables, selection of fit indices, report of results, estimation of sample size, and the fit of model. In previous ecological studies, measurements of latent variables, explanations of model parameters, and reports of key statistics were commonly overlooked, while several advanced uses of SEM had been ignored overall. With the increasing availability of data, the use of SEM holds immense potential for ecologists in the future.read more
Citations
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MonographDOI
Structural Equation Modeling
TL;DR: Structural equation modeling, structural equation modeling (SEM), Structural equation modelling (SME), this paper, Structural EDE (SDE), structural equation model (SEM)
Journal ArticleDOI
Cause and Correlation in Biology. A User's Guide to Path Analysis, Structural Equations and Causal Inference with R, Second edition, Bill Shipley. Cambridge University Press (2016), (ISBN: 978-1-107-44259-7, 314 pp., £39.99, paperback)
Journal ArticleDOI
Land use driven change in soil pH affects microbial carbon cycling processes
Ashish A. Malik,Jeremy Puissant,Kate M. Buckeridge,Tim Goodall,Nico Jehmlich,Somak Chowdhury,Hyun S. Gweon,Jodey Peyton,Kelly E. Mason,Maaike van Agtmaal,Aimeric Blaud,Ian M. Clark,Jeanette Whitaker,Richard F. Pywell,Nick Ostle,Gerd Gleixner,Robert I. Griffiths +16 more
TL;DR: It is demonstrated that microbial biomass and carbon use efficiency are reduced in human-impacted near-neutral pH soils, whereas in acidic soils, microbial growth is a bigger constraint on decomposition rates.
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A performance measurement system for industry 4.0 enabled smart manufacturing system in SMMEs- A review and empirical investigation
TL;DR: Proposed novel Smart Manufacturing Performance Measurement System (SMPMS) framework is expected to guide the practitioners in SMMEs to evaluate their SMS investments and offer more competitive benefits compared to a traditional manufacturing system.
Journal ArticleDOI
A review of the methodological misconceptions and guidelines related to the application of structural equation modeling: A Malaysian scenario
TL;DR: In this article, the authors outline four major methodological issues related to the application of structural equation modeling in Malaysia along with their respective guidelines, including probability and non-probability sampling, pre-testing and pilot study, CB-SEM and PLS -SEM, and exploratory and confirmatory factor analysis.
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