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Publication
A practical tutorial on conditional mediation analysis with generalized structured component analysis, covering method, simulation, and software.
Preprint
A public preprint develops and evaluates data-matrix-based tests of overall and nested-model fit in confirmatory factor analysis, using Monte Carlo simulation and an empirical illustration.
Publication
Bayesian networks and interpretable summary indexes are applied collaboratively to questions about recidivism and cognitive emotion regulation.
Publication
Power analysis for generalized structured component analysis, with implementation guidance using GSCA Pro.
Preprint
Collaborative longitudinal research uses machine learning, regression, and generalized structured component analysis to study psychological resources, genetic vulnerability, and depressive symptoms in later life.
Preprint
A public manuscript combining Convex GSCA summary indexes with Bayesian networks to model clinicians’ treatment recommendations, illustrated with insomnia-related decisions.
Publication
A methodological comparison of approaches to testing interactions between components.
Publication
Collaborative empirical research connecting genetic variation, trauma, cortical structures, and PTSD severity.
Publication
Regularization for structural equation models that contain both factors and components.
Publication
Interpretable composite indexes within an artificial neural network modeling framework.
Publication
Collaborative research on gene–environment pathways, cognitive development, and psychotic-like experiences.
Publication
Convex components provide interpretable composite indexes within generalized structured component analysis.
Publication
A tutorial introducing GSCA Pro and models with factors, components, or both.
Publication
How choices among SEM methods can influence the conclusions drawn from the same model and data.
Publication
A comparison of component-based SEM approaches with attention to out-of-sample prediction.
Publication
An introduction to integrated GSCA for models with both factors and components.
Publication
A methodological contribution to structural equation modeling using a data matrix-based approach.
Publication
A comparison of factor and component methods under different construct representations.
Publication
Prediction-oriented model search in generalized structured component analysis.
Publication
Evaluation and use of model fit criteria for integrated GSCA.
Publication
A multivariate methodological framework for relationships among genetic, brain, behavioral, and cognitive measurements.
Publication
An integrated approach to structural equation models containing factors and components.
Publication
Collaborative empirical research on sensory impressions, perceived value, and tourist behavior.
Publication
A comparison of GSCA and partial least squares path modeling under variance-based SEM conditions.
Publication
Assessment of overall model fit indexes in generalized structured component analysis.
Publication
Global least squares estimation as a full-information approach to path modeling.
Publication
Collaborative empirical research on education policy and the housing market.
Publication
Monte Carlo evaluation of bootstrap confidence interval methods for GSCA.
Publication
Out-of-bag prediction error as a cross-validation index for GSCA.
Publication
A collaborative review of machine learning approaches to mental-illness classification.
Publication
Collaborative development and evaluation of a Korean anxiety screening instrument.
Publication
An empirical study of relationships among interest rates, consumer sentiment, and the housing market.
Software
Free standalone software with a graphical interface for structured factor analysis.
Software
Free graphical software for structural equation modeling using generalized structured component analysis methods.
Software
A MATLAB toolbox for Monte Carlo evaluation of structural equation modeling estimators.
News
We are pleased to announce the launch of the official PsycheMatrica Lab website. The website introduces our mission and research directions in quantitative methodology for psychological and learning sciences. It brings together our publications, public preprints, research software, people, and lab news in one place. Our Publications section distinguishes peer-reviewed publications from preprints while keeping manuscript versions linked within a single record for each study. Through News, we will share updates on research, conference presentations, software releases, and developments in the lab. We invite researchers, students, and prospective collaborators to explore our work and stay connected. For research and collaboration inquiries, please contact [email protected].
News
“A Practical Guide to Conditional Mediation Analysis with GSCA: Method, Simulation, and Software” was published online in Structural Equation Modeling: A Multidisciplinary Journal. A practical tutorial on conditional mediation analysis with generalized structured component analysis, covering method, simulation, and software.
News
A public preprint of “Data-Matrix-Based Overall Goodness-of-Fit Testing for Confirmatory Factor Analysis: In-Sample Prediction Error for Observed Variables” is available. A public preprint develops and evaluates data-matrix-based tests of overall and nested-model fit in confirmatory factor analysis, using Monte Carlo simulation and an empirical illustration. The public manuscript version and its DOI are retained on the paper’s permanent record.
News
“Modeling conditional dependencies between recidivism and cognitive emotion regulation strategies among prisoners using a Bayesian network with interpretable summary indexes” was published online in PLOS One. Bayesian networks and interpretable summary indexes are applied collaboratively to questions about recidivism and cognitive emotion regulation.
News
“Combining Convex GSCA and Discrete Bayesian Networks: A Proof-of-Concept Application to Cognitive-Therapy Prioritization in CBT-I,” by Gyeongcheol Cho and Younyoung Choi, was presented as a poster at UKC 2026, Florida.
News
“Completing Partial Least Squares Path Modeling: Generalized Structured Component Analysis,” by Gyeongcheol Cho, was presented at IMPS 2026, Seoul.
News
“Extending Generalized Structured Component Analysis with Kernel Functions for Modeling Nonlinear Data,” by Hye Won Suk, Gyeongcheol Cho, and Heungsun Hwang, was presented at IMPS 2026, Seoul.
News
“Evaluation of Classical and Machine Learning-Based Missing Data Methods in Generalized Structured Component Analysis,” by Luqi He, Gyeongcheol Cho, and Heungsun Hwang, was presented at IMPS 2026, Seoul.
News
“Multilevel GSCA with Group-Level Variables: An Illustration Using GSCA Pro,” by Sunmee Kim, Gyeongcheol Cho, Heungsun Hwang, Gabriel Cepeda Carrión, Silvia Martelo-Landroguez, and José Roldán, was presented at IMPS 2026, Seoul.
News
“Second-Order Structural Equation Modeling with both Factors and Components,” by In-Hyun Baek, Gyeongcheol Cho, Florian Schuberth, and Heungsun Hwang, was presented at IMPS 2026, Seoul.
News
The IMPS 2026 program lists the poster “A Data-Matrix-Based Overall Goodness-of-Fit Test for Confirmatory Factor Analysis: In-Sample Prediction Error for Observed Variables,” by Young Ze Kim, Gyeongcheol Cho, and Hanjoe Kim, in Poster Session I on July 21 in Seoul.
News
GyeongCheol Cho gave an invited presentation, “Beyond the latent–descriptive construct dichotomy: Structural construct analysis for integrating factor- and component-based structural equation modeling,” at Ajou University, Department of Psychology, Suwon.
News
Ling Zhu presented “Data-matrix–based local diagnostics for confirmatory factor analysis: In-sample prediction error for individual observed variables,” coauthored with Gyeongcheol Cho, at ISDSA 2026. The work develops local diagnostics for confirmatory factor analysis using prediction error for individual observed variables. The meeting took place in July 2026. ISDSA Academy published the presentation recording on August 12, 2026.
News
“Evaluation of Classical and Machine Learning-Based Missing Data Methods in Generalized Structured Component Analysis,” by Luqi He, Gyeongcheol Cho, and Heungsun Hwang, was presented at ISDSA 2026, Beijing.
News
A public preprint of “Psychological resources confer greatest protection against late-life depression in genetically vulnerable adults” is available. Collaborative longitudinal research uses machine learning, regression, and generalized structured component analysis to study psychological resources, genetic vulnerability, and depressive symptoms in later life. The public manuscript version and its DOI are retained on the paper’s permanent record.
News
“Second-order structural equation modeling with both factors and components,” by In-Hyun Baek, Gyeongcheol Cho, Florian Schuberth, and Heungsun Hwang, was presented as a poster at Canadian Psychological Association’s 87th Annual National Convention, Montréal.
News
“A data-matrix-based overall goodness-of-fit test for confirmatory factor analysis,” by Y. J. Lee, Gyeongcheol Cho, and H. J. Kim, was presented as a poster at Korean Society of Psychological Measurement and Assessment, Busan.
News
GyeongCheol Cho gave an invited presentation, “Beyond the latent–descriptive construct dichotomy: Structural construct analysis for integrating factor- and component-based structural equation modeling,” at Seoul National University, Department of Psychology, Seoul.
News
“A data-matrix-based structural construct analysis for integrating factor-based and component-based structural equation modeling,” by Gyeongcheol Cho, was presented at Korean Society of Psychological Measurement and Assessment, Busan.
News
“Power Analysis in Generalized Structured Component Analysis: Implementation in GSCA Pro” was published online in Structural Equation Modeling: A Multidisciplinary Journal. Power analysis for generalized structured component analysis, with implementation guidance using GSCA Pro.
News
GyeongCheol Cho gave an invited presentation, “Constructs may or may not be latent: Two domains of structural equation modeling,” at Sogang University, Department of Psychology (online).
News
GyeongCheol Cho gave an online invited panel presentation, “Building a personalized treatment recommender that mimics clinicians’ decision-making,” at an event listed as IAAP 2026 in his CV.
News
Collaborative scholarly work involving GyeongCheol Cho received a 2026 Honorable Mention from the Korean Society of Psychological Measurement and Assessment.
News
GyeongCheol Cho gave an invited presentation, “Constructs may or may not be latent: Two domains of structural equation modeling,” at Georgia Institute of Technology, School of Psychology (online).
News
A public preprint of “Modeling conditional dependencies between recidivism and cognitive emotion regulation strategies among prisoners using a Bayesian network with interpretable summary indexes” is available. Bayesian networks and interpretable summary indexes are applied collaboratively to questions about recidivism and cognitive emotion regulation. The public manuscript version and its DOI are retained on the paper’s permanent record.
News
A public preprint of “Bayesian Networks with Interpretable Summary Indexes for Modeling Clinicians’ Decision-Making in Treatment Recommendation for Mental Disorders” is available. A public manuscript combining Convex GSCA summary indexes with Bayesian networks to model clinicians’ treatment recommendations, illustrated with insomnia-related decisions. The public manuscript version and its DOI are retained on the paper’s permanent record.
News
“Influence of genetic polymorphism and trauma on cortical structures and PTSD severity: imaging genetics generalized structured component analysis” was published online in Frontiers in Psychiatry. Collaborative empirical research connecting genetic variation, trauma, cortical structures, and PTSD severity.
News
GyeongCheol Cho presented “Constructs may or may not be latent: Studies on two domains of structural equation modeling” in the Department of Statistics seminar series at The Ohio State University.
News
“Regularized Structural Equation Modeling with Both Factors and Components” was published online in Structural Equation Modeling: A Multidisciplinary Journal. Regularization for structural equation models that contain both factors and components.
News
“Generalized structured component analysis accommodating convex components: A knowledge-based multivariate method with interpretable composite indexes,” by Gyeongcheol Cho and Heungsun Hwang, was presented at IMPS 2025, Minnesota.
News
“Comparison of missing data techniques in generalized structured component analysis,” by Luqi He, Gyeongcheol Cho, and Heungsun Hwang, was presented at IMPS 2025, Minnesota.
News
“Evaluating statistical power in generalized structured component analysis,” by Z. Shen, Gyeongcheol Cho, and Heungsun Hwang, was presented at IMPS 2025, Minnesota.
News
GyeongCheol Cho gave an invited presentation, “Introduction to Generalized Structured Component Analysis,” at Pusan National University, Department of Sports Science, Busan.
News
“Comparison of Component-Based Structural Equation Modeling Methods in Testing Component Interaction Effects” was published online in Structural Equation Modeling: A Multidisciplinary Journal. A methodological comparison of approaches to testing interactions between components.
News
GyeongCheol Cho gave an invited presentation, “Constructs may or may not be latent: Two domains of structural equation modeling,” at Ajou University, Department of Psychology, Suwon.
News
“Regularized Structural Equation Modeling with Both Factors and Components,” by Gyeongcheol Cho, J. Choi, M. Sarstedt, and Heungsun Hwang, was presented at Academy of Marketing Science Annual Conference, Montreal.
News
GyeongCheol Cho gave an invited presentation, “Constructs may or may not be latent: Two domains of structural equation modeling,” at Seoul National University, Department of Psychology, Seoul.
News
GyeongCheol Cho received the 2025 Anne Anastasi Dissertation Award from APA Division 5, Quantitative and Qualitative Methods.
News
A correction to “Generalized Structured Component Analysis Accommodating Convex Components: A Knowledge-Based Multivariate Method with Interpretable Composite Indexes” addresses section numbering and internal section references. It is linked to the original paper’s canonical record and is not counted as a new research article.
News
GyeongCheol Cho gave an invited presentation, “Introduction to convex generalized structured component analysis with interpretable composite indexes,” at Ajou University, Department of Preventive Medicine & Public Health (online).
News
eLife released an update to the Version of Record for “Gene–environment pathways to cognitive intelligence and psychotic-like experiences in children.” This entry records a version update rather than a separate paper.
News
GyeongCheol Cho delivered the Dissertation Award address at IMPS 2024 in Prague: “Constructs May or May Not Be Latent: Studies on Two Domains of Structural Equation Modeling.”
News
“Deep learning generalized structured component analysis: An interpretable artificial neural network model with composite indexes,” by Gyeongcheol Cho and Heungsun Hwang, was presented at ISDSA 2024, Vienna.
News
“Comparison of component-based SEM methods in testing component interaction effects,” by Z. Shen, Gyeongcheol Cho, and Heungsun Hwang, was presented as a poster at IMPS 2024, Prague.
News
GyeongCheol Cho gave an invited presentation, “Constructs may or may not be latent: Two domains of structural equation modeling,” at Korea University, School of Psychology, Seoul.
News
GyeongCheol Cho gave an invited presentation, “Constructs may or may not be latent: Two domains of structural equation modeling,” at Pusan National University, Department of Sports Science, Busan.
News
“Regularized integrated generalized structured component analysis,” by Heungsun Hwang and Gyeongcheol Cho, was presented at ISDSA 2024, Vienna.
News
“A two-step approach for personalized treatment recommendations in mental health using convex generalized structured component analysis and Bayesian networks,” by Gyeongcheol Cho and Younyoung Choi, was presented as a poster at IMPS 2024, Prague.
News
GyeongCheol Cho gave an invited presentation, “Structured factor analysis: A data matrix-based alternative approach to structural equation modeling,” at KAIST, School of Digital Humanities and Computational Social Sciences, Daejeon.
News
“Same model, same data, but different outcomes: Evaluating the impact of method choices in structural equation modeling” was published online in Journal of Product Innovation Management. How choices among SEM methods can influence the conclusions drawn from the same model and data.
News
The Version of Record for “Gene–environment pathways to cognitive intelligence and psychotic-like experiences in children” was released by eLife. Earlier reviewed-preprint versions remain part of the paper’s publication history.
News
“Deep Learning Generalized Structured Component Analysis: An Interpretable Artificial Neural Network Model with Composite Indexes” appeared in the March 2024 journal issue of Structural Equation Modeling: A Multidisciplinary Journal. The article was first available online on August 25, 2023; this entry records the later issue publication.
News
GyeongCheol Cho gave an invited presentation, “Deep learning generalized structured component analysis: An interpretable artificial neural network model with composite indexes,” at Penn State University, Department of Psychology (online).
News
“Generalized Structured Component Analysis Accommodating Convex Components: A Knowledge-Based Multivariate Method with Interpretable Composite Indexes” was published online in Psychometrika. Convex components provide interpretable composite indexes within generalized structured component analysis.
News
The Psychometric Society announced GyeongCheol Cho as the recipient of its 2024 Dissertation Prize. His award address followed at IMPS 2024 in Prague.
News
GyeongCheol Cho was promoted from Instructor to Assistant Professor in the Department of Psychology at The Ohio State University, effective January 1, 2024. He continues to lead PsycheMatrica Lab’s research in quantitative methodology for psychological and learning sciences.
News
GyeongCheol Cho and Heungsun Hwang received the 2024 ISDSA Best Paper Award for their work on deep learning generalized structured component analysis.
News
“GSCA Pro—Free Stand-Alone Software for Structural Equation Modeling” was published online in Structural Equation Modeling: A Multidisciplinary Journal. A tutorial introducing GSCA Pro and models with factors, components, or both.
News
A revised reviewed preprint of “Gene–environment pathways to cognitive intelligence and psychotic-like experiences in children” became available through eLife on September 6, 2023. The study examines gene–environment pathways in cognitive development and psychotic-like experiences. Later manuscript versions and the journal article are linked from the publication page.
News
GyeongCheol Cho began his tenure-track appointment as an Instructor in the Department of Psychology at The Ohio State University on August 15, 2023.
