A model selection approach to structural equation modelling: A critical evaluation and a road map for ecologists

Mario Garrido, Scott K. Hansen, Rami Yaari, Hadas Hawlena

Research output: Contribution to journalReview articlepeer-review

1 Scopus citations

Abstract

Structural equation modelling (SEM) can illuminate complex interaction networks of the sort found in ecology. However, selecting optimally complex, data-supported SEM models and quantifying their uncertainty are difficult processes. To this end, we recommend a formal model selection approach (MSA) that uses information criteria. Using a suite of numerical simulations, we compare MSA-SEM against two traditional methods. We find that MSA-SEM exhibits superior, unbiased results under the suboptimal realistic conditions characteristic of ecological studies. We then provide a road map for MSA-SEM and demonstrate its use via a case study. We illustrate the unique abilities of SEM to confirm a network structure within the realm of known causal pathways and delineate the boundaries within which MSA-SEM should be applied.

Original languageEnglish
Pages (from-to)42-53
Number of pages12
JournalMethods in Ecology and Evolution
Volume13
Issue number1
DOIs
StatePublished - 1 Jan 2022

Fingerprint

Dive into the research topics of 'A model selection approach to structural equation modelling: A critical evaluation and a road map for ecologists'. Together they form a unique fingerprint.

Cite this