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

• Published in: Methods in ecology and evolution Vol. 13; no. 1; pp. 42 - 53
• Main Authors: Garrido, Mario, Hansen, Scott K., Yaari, Rami, Hawlena, Hadas
• Format: Journal Article
• Language: English
• Published: London John Wiley & Sons, Inc 01.01.2022
• Subjects: causal analyses; Ecological effects; Ecological studies; Ecologists; Ecology; information criteria; Mathematical models; model selection; multimodal inference; Multivariate statistical analysis; network structure; path analysis; review; Structural equation modeling; structural equation modelling
• ISSN: 2041-210X; 2041-210X
• DOI: 10.1111/2041-210X.13742

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.