Results 1 to 10 of about 188,629 (284)
, 2017 Structural equation modeling (SEM) is a versatile tool for conducting a wide range of multivariate statistical analyses, including multiple regression, mediation analysis, moderation analysis, and analyses of variance and covariance. Two specialized uses of SEM that appear frequently in communication research are confirmatory factor analysis (CFA) and ...
Baumgartner, Hans, Weijters, Bert
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MethodsX, 2023 This study aimed to examine the association between place identity, sense of community, and environmental attitude. Within the theoretical framework, a connection has been identified among the variables of place identity, sense of community, and ...
Elif Kutay Karaçor, Ezgi Akçam
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Structural Equation Modeling of In silico Perturbations
Frontiers in Genetics, 2021 Gene expression is controlled by multiple regulators and their interactions. Data from genome-wide gene expression assays can be used to estimate molecular activities of regulators within a model organism and extrapolate them to biological processes in ...
Jianying Li +12 more
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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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Functional Structural Equation Model
Journal of the Royal Statistical Society Series B: Statistical Methodology, 2022 AbstractIn this article, we introduce a functional structural equation model for estimating directional relations from multivariate functional data. We decouple the estimation into two major steps: directional order determination and selection through sparse functional regression. We first propose a score function at the linear operator level, and show
Kuang-Yao, Lee, Lexin, Li
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Regularized Structural Equation Modeling [PDF]
Structural Equation Modeling: A Multidisciplinary Journal, 2016 A new method is proposed that extends the use of regularization in both lasso and ridge regression to structural equation models. The method is termed regularized structural equation modeling (RegSEM). RegSEM penalizes specific parameters in structural equation models, with the goal of creating easier to understand and simpler models.
Ross, Jacobucci +2 more
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Structural Equations Modeling [PDF]
Journal of Consumer Psychology, 2001 Peer Reviewed ; https://deepblue.lib.umich.edu/bitstream/2027.42/144267/1/jcpy83 ...
Netemeyer, Richard +9 more
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Efficient Bayesian Structural Equation Modeling in Stan
Journal of Statistical Software, 2021 Structural equation models comprise a large class of popular statistical models, including factor analysis models, certain mixed models, and extensions thereof.
Edgar C. Merkle +3 more
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Improving generalizability coefficient estimate accuracy: A way to incorporate auxiliary information
Methodological Innovations, 2018 Initially proposed by Marcoulides and further expanded by Raykov and Marcoulides, a structural equation modeling approach can be used in generalizability theory estimation.
Zhehan Jiang +3 more
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Dynamic Structural Equation Models
Structural Equation Modeling: A Multidisciplinary Journal, 2017 This article presents dynamic structural equation modeling (DSEM), which can be used to study the evolution of observed and latent variables as well as the structural equation models over time. DSEM is suitable for analyzing intensive longitudinal data where observations from multiple individuals are collected at many points in time.
Asparouhov, T. +2 more
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