Structural Equation Modeling-A Multidisciplinary Journal

Papers
(The H4-Index of Structural Equation Modeling-A Multidisciplinary Journal is 19. 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 2020-03-01 to 2024-03-01.)
ArticleCitations
Three Extensions of the Random Intercept Cross-Lagged Panel Model299
Causal Mediation Programs in R, Mplus, SAS, SPSS, and Stata66
Advances in Bayesian Model Fit Evaluation for Structural Equation Models54
On the Differences between General Cross-Lagged Panel Model and Random-Intercept Cross-Lagged Panel Model: Interpretation of Cross-Lagged Parameters and Model Choice53
Bayesian estimation of single and multilevel models with latent variable interactions49
Collapsing Categories is Often More Advantageous than Modeling Sparse Data: Investigations in the CFA Framework45
Probing Two-way Moderation Effects: A Review of Software to Easily Plot Johnson-Neyman Figures42
On the Performance of Bayesian Approaches in Small Samples: A Comment on Smid, McNeish, Miocevic, and van de Schoot (2020)37
A Comparison of Different Approaches for Estimating Cross-Lagged Effects from a Causal Inference Perspective35
Assessing Cutoff Values of SEM Fit Indices: Advantages of the Unbiased SRMR Index and Its Cutoff Criterion Based on Communality33
How to Perform Three-Step Latent Class Analysis in the Presence of Measurement Non-Invariance or Differential Item Functioning30
Not Positive Definite Correlation Matrices in Exploratory Item Factor Analysis: Causes, Consequences and a Proposed Solution29
Effects of Cross-loadings on Determining the Number of Factors to Retain27
Computational Options for Standard Errors and Test Statistics with Incomplete Normal and Nonnormal Data in SEM26
Sample Size Recommendations for Continuous-Time Models: Compensating Shorter Time Series with Larger Numbers of Persons and Vice Versa25
Item Meaning and Order as Causes of Correlated Residuals in Confirmatory Factor Analysis24
The Use of Traditional and Causal Estimators for Mediation Models with a Binary Outcome and Exposure-Mediator Interaction23
Measurement in Intensive Longitudinal Data21
Multilevel Analysis of Mediation, Moderation, and Nonlinear Effects in Small Samples, Using Expected a Posteriori Estimates of Factor Scores20
0.022945880889893