Structural Equation Modeling-A Multidisciplinary Journal

Papers
(The H4-Index of Structural Equation Modeling-A Multidisciplinary Journal is 16. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2021-04-01 to 2025-04-01.)
ArticleCitations
Comparison of Three Approaches to Class Enumeration in Growth Mixture Modeling when Time Structures are Variant Across Latent Classes73
A Growth of Hierarchical Autoregression Model for Capturing Individual Differences in Changes of Dynamic Characteristics of Psychological Processes56
Research Design and Model Estimation Under the Partially Confirmatory Latent Variable Modeling Framework with Multi-Univariate Bayesian Lassos53
Model Estimation Approaches for Fully-Latent Principal Stratification with Small Samples52
Review of An Introduction to Modern Modeling Methods49
Python Packages for Exploratory Factor Analysis42
Equal Precision Measurement Structural Models41
Latent Class Analysis with Measurement Invariance Testing: Simulation Study to Compare Overall Likelihood Ratio vs Residual Fit Statistics Based Model Selection39
Review of Educational and Psychological Measurement38
Application of Associative Discrete-Time Survival Analysis Using Latent Transition Specification26
Analyzing Longitudinal Multirater Data with Individually Varying Time Intervals24
Model Fit Indices for Random Effects Models: Translating Model Fit Ideas from Latent Growth Curve Models24
Flexible Extensions to Structural Equation Models Using Computation Graphs20
Testing Mean and Covariance Structures with Reweighted Least Squares18
Review of Applied Univariate, Bivariate, and Multivariate Statistics Using Python by Daniel Denis18
Evaluating Causal Dominance of CTmeta-Analyzed Lagged Regression Estimates16
Structured Factor Analysis: A Data Matrix-Based Alternative Approach to Structural Equation Modeling16
Mixed-Effects Trait-State-Occasion Model: Studying the Psychometric Properties and the Person–Situation Interactions of Psychological Dynamics16
PolychoricRM: A Computationally Efficient R Function for Estimating Polychoric Correlations and their Asymptotic Covariance Matrix16
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