The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Using structural equation modeling to investigate relationships among ecological variables
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“SEM is a multicomponent statistical process which can allow researchers to construct theoretical models, such as the CBPM, and test to see if the relationships set out in such theories fit a dataset, providing evidence for, or against, the theory as being a useful explanatory framework (Malaeb et al., 2000).”
From Testing Mindfulness Mechanisms of Action on the Stress and Burnout of Social Workers (2024) · cites this paper as Malaeb et al., 2000
Citations
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“While similar to GLMs in that it examines linear causal relationships among variables, SEM assumes that there is an underlying mechanism which leads to a theoretical covariance structure among variables (Malaeb et al., 2000).”
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“Structural equation modeling (SEM) is an advanced multivariate statistical approach with which a researcher can set up theoretical concepts; test multivariate relationships within and between observed (variables that can be measured directly) and latent (variables that cannot be measured directly) variables; and corro…”
BackgroundLampi, M. A. (2005) · UWSpace (University of Waterloo) · Cited by 4
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“Second, SEM can model the relationships between observed and latent variables (Malaeb, Summers, and Pugesek 2000).”
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“Model fit was summarized using CFI, TLI, SRMR, AIC, BIC, and the chi-square goodness-of-fit test [27,48,49].”
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“Integrative approaches are increasingly needed to understand how agricultural management practices influence soil structural functions because aggregate stability results from the interaction of multiple physical, chemical, and biological processes [26,27].”
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Metadata
- Authors
- Malaeb, Z. A., Summers, J. K., & Pugesek, B. H.
- Affiliations
- United States Geological Survey (US)
- Environmental Protection Agency (US)
- ORCID
- Summers, J. Kevin
- Venue
- Environmental and Ecological Statistics
- Published
- 2000-03
- Volume
- 7
- Issue
- 1
- Pages
- 93-111
- ISSN
- 1352-8505 (ISSN-L)
- 1573-3009
- OpenAlex
- W1574417742
- Cited by
- 178
- References
- 22
- Citations by year
- 2026: 7 · 2025: 22 · 2024: 19 · 2023: 11 · 2022: 16 · 2021: 11 · 2020: 12 · 2019: 4 · 2018: 10 · 2017: 13 · 2016: 7 · 2015: 5 · 2014: 5 · 2013: 5 · 2012: 9
- FWCI
- 1.81
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- Environmental and Ecological Statistics (publishedVersion)
- Funders
- U.S. Environmental Protection Agency
- Topics
- Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Physical Sciences › Environmental Science › Water Science and Technology › Water Quality and Pollution Assessment
- Keywords
- sediment contamination, natural variation, biodiversity, growth potential, estuarine ecosystems, indirect effects, latent variables, environmental monitoring, ecosystem health
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