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Estimating Local Structural Equation Models [PDF]
Journal of Intelligence, 2023 Local structural equation models (LSEM) are structural equation models that study model parameters as a function of a moderator. This article reviews and extends LSEM estimation methods and discusses the implementation in the R package sirt.
Alexander Robitzsch
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Products of Variables in Structural Equation Models. [PDF]
Struct Equ Modeling, 2023 A general method is introduced in which variables that are products of other variables in the context of a structural equation model (SEM) can be decomposed into the sources of variance due to the multiplicands. The result is a new category of SEM which we call a Products of Variables Model (PoV).
Boker S +6 more
europepmc +4 more sources
SEMgsa: topology-based pathway enrichment analysis with structural equation models [PDF]
BMC Bioinformatics, 2022 Background Pathway enrichment analysis is extensively used in high-throughput experimental studies to gain insight into the functional roles of pre-defined subsets of genes, proteins and metabolites.
Mario Grassi, Barbara Tarantino
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Choice Function-Based Hyper-Heuristics for Causal Discovery under Linear Structural Equation Models [PDF]
BiomimeticsCausal discovery is central to human cognition, and learning directed acyclic graphs (DAGs) is its foundation. Recently, many nature-inspired meta-heuristic optimization algorithms have been proposed to serve as the basis for DAG learning.
Yinglong Dang +2 more
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General guidance for custom-built structural equation models [PDF]
One Ecosystem, 2022 Structural Equation Modelling (SEM) represents a quantitative methodology for specifying and evaluating causal network hypotheses. The application of SEM typically involves the use of specialised software packages that implement estimation procedures and
James Grace
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Modeling Model Misspecification in Structural Equation Models
Stats, 2023 Structural equation models constrain mean vectors and covariance matrices and are frequently applied in the social sciences. Frequently, the structural equation model is misspecified to some extent.
Alexander Robitzsch
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Implementation Aspects in Regularized Structural Equation Models
Algorithms, 2023 This article reviews several implementation aspects in estimating regularized single-group and multiple-group structural equation models (SEM). It is demonstrated that approximate estimation approaches that rely on a differentiable approximation of non ...
Alexander Robitzsch
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Model-Robust Estimation of Multiple-Group Structural Equation Models
Algorithms, 2023 Structural equation models (SEM) are widely used in the social sciences. They model the relationships between latent variables in structural models, while defining the latent variables by observed variables in measurement models.
Alexander Robitzsch
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A 'Weight of Evidence' approach to evaluating structural equation models [PDF]
One Ecosystem, 2020 It is possible that model selection has been the most researched and most discussed topic in the history of both statistics and structural equation modeling (SEM).
James Grace
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Hierarchical Structural Analysis Method for Complex Equation-Oriented Models
Mathematics, 2021 Structural analysis is a method for verifying equation-oriented models in the design of industrial systems. Existing structural analysis methods need flattening of the hierarchical models into an equation system for analysis.
Chao Wang +6 more
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