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Xinya Liang & Chunhua Cao. (2023) Small-Variance Priors in Bayesian Factor Analysis with Ordinal Data. The Journal of Experimental Education 91:4, pages 739-764.
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Benedikt Friemelt, Christian Bloszies, Maximilian S. Ernst, Aaron Peikert, Andreas M. Brandmaier & Tobias Koch. (2023) On the Performance of Different Regularization Methods in Bifactor-(S-1) Models with Explanatory Variables—Caveats, Recommendations, and Future Directions. Structural Equation Modeling: A Multidisciplinary Journal 30:4, pages 560-573.
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Jannik H. Orzek, Manuel Arnold & Manuel C. Voelkle. (2023) Striving for Sparsity: On Exact and Approximate Solutions in Regularized Structural Equation Models. Structural Equation Modeling: A Multidisciplinary Journal 0:0, pages 1-18.
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Philipp Sterner & David Goretzko. (2023) Exploratory Factor Analysis Trees: Evaluating Measurement Invariance Between Multiple Covariates. Structural Equation Modeling: A Multidisciplinary Journal 0:0, pages 1-16.
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Julie De Jonckere & Yves Rosseel. (2023) A Model-Based Shrinkage Target to Avoid Non-convergence in Small Sample SEM. Structural Equation Modeling: A Multidisciplinary Journal 0:0, pages 1-15.
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Murat Genç & M. Revan Özkale. (2023) Regularization and variable selection with triple shrinkage in linear regression: a generalization of lasso. Communications in Statistics - Simulation and Computation 0:0, pages 1-23.
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Mark de Rooij, Julian D. Karch, Marjolein Fokkema, Zsuzsa Bakk, Bunga Citra Pratiwi & Henk Kelderman. (2023) SEM-Based Out-of-Sample Predictions. Structural Equation Modeling: A Multidisciplinary Journal 30:1, pages 132-148.
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Jinsong Chen. (2022) A Generalized Partially Confirmatory Factor Analysis Framework with Mixed Bayesian Lasso Methods. Multivariate Behavioral Research 57:6, pages 879-894.
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Jinsong Chen. (2022) Partially Confirmatory Approach to Factor Analysis with Bayesian Learning: A LAWBL Tutorial. Structural Equation Modeling: A Multidisciplinary Journal 29:5, pages 800-816.
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Julie De Jonckere & Yves Rosseel. (2022) Using Bounded Estimation to Avoid Nonconvergence in Small Sample Structural Equation Modeling. Structural Equation Modeling: A Multidisciplinary Journal 29:3, pages 412-427.
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Po-Hsien Huang. (2022) Penalized Least Squares for Structural Equation Modeling with Ordinal Responses. Multivariate Behavioral Research 57:2-3, pages 279-297.
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Erik–Jan van Kesteren & Daniel L. Oberski. (2022) Flexible Extensions to Structural Equation Models Using Computation Graphs. Structural Equation Modeling: A Multidisciplinary Journal 29:2, pages 233-247.
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Florian Scharf, Jana Pförtner & Steffen Nestler. (2021) Can Ridge and Elastic Net Structural Equation Modeling be Used to Stabilize Parameter Estimates when Latent Factors are Correlated?. Structural Equation Modeling: A Multidisciplinary Journal 28:6, pages 928-940.
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Philippe Goldammer, Hubert Annen, Christopher Lienhard & Klaus Jonas. (2021) An examination of model fit and measurement invariance of general mental ability and personality measures used in the multilingual context of the Swiss Armed Forces: A Bayesian structural equation modeling approach. Military Psychology 0:0, pages 1-18.
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Jinsong Chen. (2021) A Bayesian Regularized Approach to Exploratory Factor Analysis in One Step. Structural Equation Modeling: A Multidisciplinary Journal 28:4, pages 518-528.
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Bing Cai Kok, Ji Sok Choi, Hyelim Oh & Ji Yeh Choi. (2021) Sparse Extended Redundancy Analysis: Variable Selection via the Exclusive LASSO. Multivariate Behavioral Research 56:3, pages 426-446.
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Ke-Hai Yuan & Fang Liu. (2021) Which Method is More Reliable in Performing Model Modification: Lasso Regularization or Lagrange Multiplier Test?. Structural Equation Modeling: A Multidisciplinary Journal 28:1, pages 69-81.
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Steffen Zitzmann, Oliver Lüdtke, Alexander Robitzsch & Martin Hecht. (2021) On the Performance of Bayesian Approaches in Small Samples: A Comment on Smid, McNeish, Miocevic, and van de Schoot (2020). Structural Equation Modeling: A Multidisciplinary Journal 28:1, pages 40-50.
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Timothy Hayes & Satoshi Usami. (2020) Factor Score Regression in Connected Measurement Models Containing Cross-Loadings. Structural Equation Modeling: A Multidisciplinary Journal 27:6, pages 942-951.
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Xinya Liang, Yanyun Yang & Chunhua Cao. (2020) The Performance of ESEM and BSEM in Structural Equation Models with Ordinal Indicators. Structural Equation Modeling: A Multidisciplinary Journal 27:6, pages 874-887.
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Xinya Liang & Ross Jacobucci. (2020) Regularized Structural Equation Modeling to Detect Measurement Bias: Evaluation of Lasso, Adaptive Lasso, and Elastic Net. Structural Equation Modeling: A Multidisciplinary Journal 27:5, pages 722-734.
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Axel Mayer, Johannes Zimmermann, Jürgen Hoyer, Simone Salzer, Jörg Wiltink, Eric Leibing & Falk Leichsenring. (2020) Interindividual Differences in Treatment Effects Based on Structural Equation Models with Latent Variables: An EffectLiteR Tutorial. Structural Equation Modeling: A Multidisciplinary Journal 27:5, pages 798-816.
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Xinya Liang & Yong Luo. (2020) A Comprehensive Comparison of Model Selection Methods for Testing Factorial Invariance. Structural Equation Modeling: A Multidisciplinary Journal 27:3, pages 380-395.
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Po-Hsien Huang. (2020) Postselection Inference in Structural Equation Modeling. Multivariate Behavioral Research 55:3, pages 344-360.
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Daniel J. Bauer, William C. M. Belzak & Veronica T. Cole. (2020) Simplifying the Assessment of Measurement Invariance over Multiple Background Variables: Using Regularized Moderated Nonlinear Factor Analysis to Detect Differential Item Functioning. Structural Equation Modeling: A Multidisciplinary Journal 27:1, pages 43-55.
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Jonas Christoffer Lindstrøm & Fredrik A. Dahl. (2020) Model Selection with Lasso in Multi-group Structural Equation Models. Structural Equation Modeling: A Multidisciplinary Journal 27:1, pages 33-42.
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Sarfaraz Serang & Ross Jacobucci. (2020) Exploratory Mediation Analysis of Dichotomous Outcomes via Regularization. Multivariate Behavioral Research 55:1, pages 69-86.
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Yubin Tian & Ke-Hai Yuan. (2019) Mean and Variance Corrected Test Statistics for Structural Equation Modeling with Many Variables. Structural Equation Modeling: A Multidisciplinary Journal 26:6, pages 827-846.
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Erik-Jan van Kesteren & Daniel L. Oberski. (2019) Exploratory Mediation Analysis with Many Potential Mediators. Structural Equation Modeling: A Multidisciplinary Journal 26:5, pages 710-723.
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Florian Scharf & Steffen Nestler. (2019) Should Regularization Replace Simple Structure Rotation in Exploratory Factor Analysis?. Structural Equation Modeling: A Multidisciplinary Journal 26:4, pages 576-590.
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Augustin Kelava & Holger Brandt. (2019) A Nonlinear Dynamic Latent Class Structural Equation Model. Structural Equation Modeling: A Multidisciplinary Journal 26:4, pages 509-528.
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Holger Brandt, Jenna Cambria & Augustin Kelava. (2018) An Adaptive Bayesian Lasso Approach with Spike-and-Slab Priors to Identify Multiple Linear and Nonlinear Effects in Structural Equation Models. Structural Equation Modeling: A Multidisciplinary Journal 25:6, pages 946-960.
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Steffen Zitzmann. (2018) A Computationally More Efficient and More Accurate Stepwise Approach for Correcting for Sampling Error and Measurement Error. Multivariate Behavioral Research 53:5, pages 612-632.
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Ross Jacobucci & Kevin J. Grimm. (2018) Comparison of Frequentist and Bayesian Regularization in Structural Equation Modeling. Structural Equation Modeling: A Multidisciplinary Journal 25:4, pages 639-649.
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Xinya Liang, Yanyun Yang & Jiajing Huang. (2018) Evaluation of Structural Relationships in Autoregressive Cross-Lagged Models Under Longitudinal Approximate Invariance:A Bayesian Analysis. Structural Equation Modeling: A Multidisciplinary Journal 25:4, pages 558-572.
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Erin H. Arruda & Peter M. Bentler. (2017) A Regularized GLS for Structural Equation Modeling. Structural Equation Modeling: A Multidisciplinary Journal 24:5, pages 657-665.
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Sarfaraz Serang, Ross Jacobucci, Kim C. Brimhall & Kevin J. Grimm. (2017) Exploratory Mediation Analysis via Regularization. Structural Equation Modeling: A Multidisciplinary Journal 24:5, pages 733-744.
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Sierra A. Bainter. (2017) Bayesian Estimation for Item Factor Analysis Models with Sparse Categorical Indicators. Multivariate Behavioral Research 52:5, pages 593-615.
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