Publications
Accepted/In press
Cho, G., & Hwang, H. (in press). Generalized structured component analysis accommodating convex components: A knowledge-based multivariate method with interpretable composite indexes. Psychometrika.
Hwang, H., Cho, G., & Choo, H. (in press). GSCA Pro—Free stand-alone software for structural equation modeling. Structural Equation Modeling: A Multidisciplinary Journal.
Sarstedt, M., Adler, S., Ringle, C. M., Cho, G., Diamantopoulos, A., Hwang, H., & Liengaard, B. (in press). Same model, same data, but different outcomes: Evaluating the impact of method choices in structural equation modeling. Journal of Product Innovation Management.
2024
Wiberg, M., Kim, J-S., & Hwang, H., Wu, H., & Sweet, T. (2024). Quantitative Psychology: The 88th Annual Meeting of the Psychometric Society, Maryland, USA, 2023. Cham, Switzerland: Springer.
Park, J., Lee, E., Cho, G., Hwang, H., Kim, B., Kim, G., Joo, Y., & Cha, J. (2024). Gene-environment pathways to cognitive intelligence and psychotic-like experiences in children. eLife, 12, 88117.
Cho, G., & Hwang, H. (2024). Deep learning generalized structured component analysis: An interpretable artificial neural network model with composite indexes. Structural Equation Modeling: A Multidisciplinary Journal, 31, 265-279.
2023
Cho, G., & Hwang, H. (2023). Structured factor analysis: A data matrix-based alternative approach to structural equation modeling. Structural Equation Modeling: A Multidisciplinary Journal, 30, 364-377.
Cho, G., Kim, S., Lee, J., Hwang, H., Sarstedt, M., & Ringle, C. M. (2023). A comparative study of the predictive power of component-based approaches to structural equation modeling. European Journal of Marketing, 57, 1641-1661.
Hwang, H., Sarstedt, M., Cho, G., Choo, H., & Ringle, C. M. (2023). A primer on integrated generalized structured component analysis. European Business Review, 35, 261-284.
Wiberg, M., Molenaar, D., González, J., Kim, J-S., & Hwang, H. (2023). Quantitative Psychology: The 87th Annual Meeting of the Psychometric Society, Bologna, Italy, 2022. Cham, Switzerland: Springer.
2022
Wiberg, M., Molenaar, D., González, J., Kim, J-S., & Hwang, H. (2022). Quantitative Psychology: The 86th Annual Meeting of the Psychometric Society, Virtual, 2021, Cham, Switzerland: Springer.
Pascoal T., Chamoun, M., Lax, E., Wey, H.-Y., Shin, M., Ng, K., Kang, M., Mathotaarachchi, S., Benedet, A., Therriault, J., Schroeder, F., DuBois, J., Hightower, B., Gilbert, T., Zurcher, N., Wang, C., Hopewell, R., Chakravarty, M., Savard, M., Thomas, E., Farzin, S., Salaciak, A., Tullo, S., Cuello, A., Soucy, J.-P., Massarweh, G., Hwang, H., Kobayashi, E., Hyman, B., Dickerson, B., Szyf, M., Gauthier, S., Hooker, J., & Rosa-Neto, P. (2022). [11C]Martinostat PET analysis reveals reduced HDAC I availability in Alzheimer’s disease. Nature Communications. 13(1):4171.
Cho, G., Hwang, H., Sarstedt, M., & Ringle, C. M. (2022). A prediction-oriented specification search algorithm for generalized structured component analysis. Structural Equation Modeling: A Multidisciplinary Journal, 29, 611-619.
Hwangbo, S., Lee, S., Lee, S., Hwang, H., Kim, I., & Park, T. (2022). Kernel-based hierarchical structural component models for pathway analysis. Bioinformatics, 38, 3078–3086.
Ryoo, J. H., Park, S., Kim, S., & Hwang, H. (2022). gscaLCA in R: Fitting fuzzy clustering analysis incorporated with generalized structured component analysis. Computer Modeling in Engineering & Sciences, 132, 801-822.
Cho, G., Sarstedt, M., & Hwang, H. (2022). A comparative evaluation of factor- and component-based structural equation modeling approaches under (in)correct construct representations. British Journal of Mathematical and Statistical Psychology, 75, 220-251.
Kim, S., & Hwang, H. (2022). Evaluation of prediction-oriented model selection metrics for extended redundancy analysis. Frontiers in Psychology, Section Quantitative Psychology and Measurement, 13, 821897.
Cho, G., Schlägel, C., Hwang, H., Choi, Y., Sarstedt, M., & Ringle, C. M. (2022). Integrated generalized structured component analysis: On the use of model fit criteria in international management research. Management International Review, 62, 569–609.
2021
Hwang, H., Ringle, C. M., & Sarstedt, M. (2021). Guest editorial: Special issue on composite-based structural equation modeling. The DATABASE for Advances in Information Systems, 52 (SI), 7–9.
Chinchani, A., Menon, M., Roes, M., Hwang, H., Allen, P., Bell, V., Bless, J., Bortolon, C., Cella, M., Fernyhough, C., Garrison, J., Kozáková, E., Laroi, F., Moffatt, J., Say, N., Suzuki, M., Toh, W., Zaytseva, Y., Rossell, S. L., Moseley, P., & Woodward, T. (2021). Item-specific overlap between hallucinatory experiences and cognition in the general population: A three-step multivariate analysis of international multi-site data. Cortex, 145 (December), 131-144.
Kim, S., & Hwang, H. (2021). Model-based recursive partitioning of extended redundancy analysis with an application to nicotine dependence among US adults. British Journal of Mathematical and Statistical Psychology, 74(3), 567-590.
Fakfare, P., Cho, G., Hwang, H., & Manosuthi, N. (2021). Examining the sensory impressions, value perception, and behavioral responses of tourists: the case of floating markets in Thailand. Journal of Travel & Tourism Marketing, 38(7), 666-681.
Hwang, H., Cho, G., Jung, K., Falk, C., Flake, J., Jin, M. J., & Lee, S. H. (2021). An approach to structural equation modeling with both factors and components: Integrated generalized structured component analysis. Psychological Methods, 26(3), 273–294.
Hwang, H., Cho, G., Jin, M. J., Ryoo, J. H., Choi, Y., & Lee, S. H. (2021). A knowledge-based multivariate statistical method for examining gene-brain-behavioral/cognitive relationships: Imaging genetics generalized structured component analysis. PLoS ONE, 16(3): e0247592.
Lee, J., & Hwang, H. (2021). The hierarchy-of-effects model and prelaunch forecasting. International Journal of Market Research, 63, 368-385.
2020
Cho, G., Hwang, H., Sarstedt, M., & Ringle, C. M. (2020). Cutoff criteria for overall model fit indexes in generalized structured component analysis. Journal of Marketing Analytics, 8,189–202.
Choi, S., Lee, S., Huh, I., Hwang, H., & Park, T. (2020). HisCoM-G×E: Hierarchical structural component analysis of gene-based gene-environment interactions. International Journal of Molecular Sciences, 21, 6724.
Hwang, H., & Cho, G. (2020). Global least squares path modeling: A full-information alternative to partial least squares path modeling. Psychometrika, 85, 947-972.
Kim, S., Lee, S., Cardwell, R., Kim, Y., Park, T., & Hwang, H. (2020). An application of regularized extended redundancy analysis via generalized estimating equations to the study of co-occurring substance use among US adults. In M. Wiberg, D. Molenaar, J. González, U. Bockenholt, & J.-S. Kim (Eds.). Quantitative Psychology. IMPS 2019 (pp. 365-376). Springer, Cham.
Choi, J. Y., & Hwang, H. (2020). Bayesian generalized structured component analysis. British Journal of Mathematical and Statistical Psychology, 73, 347–373.
Choi, J. Y., Kyung, M., Hwang, H., & Park, J-H. (2020). Bayesian extended redundancy analysis: a Bayesian approach to component-based regression with dimension reduction. Multivariate Behavioral Research, 55, 30-48.
Sarstedt, M., & Hwang, H. (2020). Advances in composite-based structural equation modeling. Behaviormetrika, 47, 213–217.
Hwang, H., Sarstedt, M., Cheah, J. H., & Ringle, C. M. (2020). A concept analysis of methodological research on composite-based structural equation modeling: Bridging PLSPM and GSCA. Behaviormetrika, 47, 219–241.
2019
Cho, G., Jung, K., & Hwang, H. (2019). Out-of-bag prediction error: A cross validation index for generalized structured component analysis. Multivariate Behavioral Research, 54, 505-513.
Lee, S., Kim, S., Kim, Y., Oh, B., Hwang, H., & Park, T. (2019). Pathway analysis of rare variants for the clustered phenotypes by using hierarchical structured components analysis. BMC Medical Genomics, 12, Article number: 100.
Murphy, T. J., Hwang, H., Kramer, M. S., Martin, R. M., Oken, E., & Yang, S. (2019). Assessment of eating attitudes and dieting behaviours in healthy children: Confirmatory factor analysis of the Children’s Eating Attitudes Test. International Journal of Eating Disorders, 52, 669-680.
Pascoal, T. A., Mathotaarachchi, S., Kang, M. S., Shin, M., Park, A. Y., Parent, M. J., Benedet, A. L., Mohades, S., Soucy, J.P., Hwang, H., Cuello, C., Misic, B., Aston, J., Gauthier, S., & Rosa-Neto, P. (2019). Aβ-induced vulnerability propagates via the brain’s default mode network. Nature Communications, 10, Article number: 2353.
Lee, J., Hwang, H., Tran, A., & Keel, A. (2019). The mediation effect of inertia on service duration. Journal of Applied Structural Equation Modeling , 3, 1-14.
2018
Choi, S., Lee, S., Kim, Y., Hwang, H., & Park, T. (2018). HisCoM-GGI: Hierarchical structural component analysis of gene-gene interactions. Journal of Bioinformatics and Computational Biology, 16, 1840026-1 - 1840026-25.
Jung, K., Panko, P., Lee, J., & Hwang, H. (2018). A comparative study on the performance of GSCA and CSA in parameter recovery for structural equation models with ordinal observed variables. Frontiers in Psychology - Quantitative Psychology and Measurement, 9, 2461.
Lee, S., Kim, Y., Choi, S., Hwang, H., & Park, T. (2018). Pathway-based approach using hierarchical components of rare variants to analyze multiple phenotypes. BMC Bioinformatics, 19, 79.
Takane, Y., & Hwang, H. (2018). Comparisons among several consistent estimators of structural equation models. Behaviormetrika, 45, 157-188.
Choi, J. Y., Hwang, H., & Timmerman, M. (2018). Functional parallel factor analysis for functions of one- and two-dimensional arguments. Psychometrika, 83, 1-20.
Ellis, B. K., Hwang, H., Savage, P. E., Pan, B.-Y., Cohen, A. J., & Brown, S. (2018). Identifying style-types in a sample of musical improvisations using dimensional reduction and cluster analysis. Psychology of Aesthetics, Creativity, and the Arts, 12, 110-122.
Choi, J. Y., Yang, S., Tenenhaus, A., & Hwang, H. (2018). Three-way generalized structured component analysis. In M. Wiberg, S. Culpepper, R. Janssen, J. González, & D. Molenaar (Eds.). Quantitative Psychology. IMPS 2017 (pp. 195-209). Springer.
2017
Hwang, H., Takane, Y., & Jung, K. (2017). Generalized structured component analysis with uniqueness terms for accommodating measurement error. Frontiers in Psychology - Quantitative Psychology and Measurement, 8, 2137.
Ryoo, J. H., & Hwang, H. (2017). Model evaluation in generalized structured component analysis using confirmatory tetrad analysis. Frontiers in Psychology - Quantitative Psychology and Measurement, 8, 916.
Kim, S., Choi, J. Y., & Hwang, H. (2017). Two-way regularized fuzzy clustering of multiple correspondence analysis. Multivariate Behavioral Research, 52, 31-46.
Kim, S., Cardwell, R., & Hwang, H. (2017). Using R package gesca for generalized structured component analysis. Behaviormetrika, 44, 3-23.
Choi, J. Y., Hwang, H., Yamamoto, M., Jung, K., & Woodward, T. S. (2017). A unified approach to functional principal component analysis and functional multiple-set canonical correlation analysis. Psychometrika, 82, 427-441.
Yamamoto, M., & Hwang, H. (2017). Dimension-reduced clustering of functional data via subspace separation. Journal of Classification, 34, 294-326.
Lee, J., Hwang, H., & Tran, A. (2017). Repositioning via abstraction. In A. Gneezy, V. Griskevicius, & P. Williams (Eds.). Advances in Consumer Research, Vol. 45 (pp. 451- 453). Association for Consumer Research. Duluth, MN.
2016
Suk, H. W., & Hwang, H. (2016). Functional generalized structured component analysis. Psychometrika, 81, 940-968.
Lee, S., Choi, S., Kim, Y. J., Kim, B.-J., T2D-Genes Consortium, Hwang, H., & Park, T. (2016). Pathway-based approach using hierarchical components of collapsed rare variants. Bioinformatics, 32, i586-i594.
Zhou, L., Takane, Y., & Hwang, H. (2016). Dynamic GSCANO (Generalized Structured Canonical Correlation Analysis) with applications to the analysis of effective connectivity in functional neuroimaging data. Computational Statistics and Data Analysis, 101, 93-109.
Jung, K., Takane, Y., Hwang, H., & Woodward, T. S. (2016). Multilevel dynamic generalized structured component analysis for brain connectivity analysis in functional neuroimaging data. Psychometrika, 81, 565-581.
DeSarbo, W. S., Hwang, H., & Jedidi, K. (2016). Redundancy analysis. Wiley StatsRef: Statistics Reference Online (pp. 1–18). John Wiley & Sons.
2015
DeSarbo, W., Hwang, H., Blank, A. S., & Kappe, E. (2015). Constrained stochastic extended redundancy analysis. Psychometrika, 80, 516-534.
Hwang, H., Takane, Y., & Tenenhaus, A. (2015). An alternative estimation procedure for partial least squares path modeling. Behaviormetrika, 42, 63-78.
Tan, T., Choi, J. Y., & Hwang, H. (2015). Fuzzy clusterwise functional extended redundancy analysis. Behaviormetrika, 42, 37-62.
Romdhani, H., Hwang, H., Paradis, G., Roy-Gagnon, M.-H., & Labbe, A. (2015). Pathway-based association study of multiple candidate genes and multiple traits using structural equation models. Genetic Epidemiology, 39, 101-113.
Hwang, H., Suk, H. W., Takane, Y., Lee, J.-H., & Lim, J. (2015). Generalized functional extended redundancy analysis. Psychometrika, 80, 101-125.
Choi, S., Lee, S., Huh, I., Hwang, H., & Park, T. (2015). Competitive pathway analysis using structural equation models (CPA-SEM) for gene expression data. Proceedings of IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 1351-1358.
2014
Hwang, H., & Takane, Y. (2014). Generalized structured component analysis: A component-based approach to structural equation modeling. Boca Raton, FL: Chapman & Hall/CRC Press. (2015 Winner of the Sugiyama Meiko Award (Publication Award) of the Behaviormetric Society)
Woodward, T. S., Jung, K., Smith, G. N., Hwang, H., Barr, A. M., Procyshyn, R. M., Flynn, S. W., van der Gaag, M., & Honer, W. G. (2014). Symptom changes in five dimensions of the positive and negative syndrome scales in refractory psychosis. European Archives of Psychiatry and Clinical Neuroscience, 264, 673–682.
Woodward, T. S., Jung, K., Hwang, H., Yin, J., Taylor L., Menon, M., Peters, E., Kuipers, E., Waters, F., Lecomte, T., Sommer, I., Daalman, K., van Lutterveld, R., Hubl, D., Kindler, J., Homan, P., Badcock, J. C., Chhabra, S., Cella, M., Keedy, S., Allen, P., Mechelli, A., Preti, A., Siddi, S., & Erickson, D. (2014). Symptom dimensions of the psychotic symptom rating scales (PSYRATS) in psychosis: A multi-site study. Schizophrenia Bulletin, 40 (Suppl 4), S265-S274.
Yamamoto, M., & Hwang, H. (2014). A general formulation of cluster analysis with dimension reduction and subspace separation. Behaviormetrika, 41, 115-129.
2013
Suk, H. W., Choi, J. Y., & Hwang, H. (2013). Hierarchically structured fuzzy c-means clustering. Behaviormetrika, 40, 1-17.
Park, K., Suk, H. W., Hwang, H., & Lee, J-H. (2013). A functional analysis of deception detection of a mock crime using infrared thermal imaging and the concealed information test. Frontiers in Human Neuroscience, 7, 70.
Tan, T., Suk, H. W., Hwang, H., & Lim, J. (2013). Functional fuzzy clusterwise regression analysis. Advances in Data Analysis and Classification, 7, 57-82.
Hwang, H., Jung, K., Takane, Y., & Woodward, T. (2013). A unified approach to multiple-set canonical correlation analysis and principal components analysis. British Journal of Mathematical and Statistical Psychology, 66, 308-321.
2012
Jung, K., Takane, Y., Hwang, H., & Woodward, T. (2012). Dynamic GSCA (Generalized Structured Component Analysis) with applications to the analysis of effective connectivity in functional neuroimaging data. Psychometrika, 77, 827-848.
Hwang, H., Suk, H. W., Lee, J.-H., Moskowitz, D. S., & Lim, J. (2012). Functional extended redundancy analysis. Psychometrika, 77, 524-542.
Hwang, H., Jung, K., Takane, Y., & Woodward, T. (2012). Functional multiple-set canonical correlation analysis. Psychometrika, 77, 48-64.
2011
Rogers, M., Hwang, H., Toplak, M., Weiss, M., & Tannock, R. (2011). Inattention, working memory, and academic achievement in adolescents referred for Attention-Deficit/Hyperactivity Disorder (ADHD). Child Neuropsychology, 17, 444-458.
Takane, Y., Jung, K., & Hwang, H. (2011). Regularized reduced rank growth curve models. Computational Statistics and Data Analysis, 55, 1041-1052.
2010
Hwang, H., & Tomiuk, M. A. (2010). Fuzzy clusterwise quasi-likelihood generalized linear models. Advances in Data Analysis and Classification, 4, 255 -270.
Hwang, H., Dillon, W. R., & Takane, Y. (2010). Fuzzy cluster multiple correspondence analysis. Behaviormetrika, 37, 111-133.
Hwang, H., Malhotra, N. K., Kim, Y., Tomiuk, M. A., & Hong, S. (2010). A comparative study on parameter recovery of three approaches to structural equation modeling. Journal of Marketing Research, 47 (Aug), 699-712.
Takane, Y., Jung, K., & Hwang, H. (2010). An acceleration method for ten Berge et al.’s algorithm for orthogonal INSCAL. Computational Statistics, 25, 409-428.
Hwang, H., Ho, R. M., & Lee, J. (2010). Generalized structured component analysis with latent interactions. Psychometrika, 75, 228-242.
Hwang, H., & Dillon, W. R. (2010). Simultaneous two-way clustering of multiple correspondence analysis. Multivariate Behavioral Research, 45, 186-208.
Suk, H. W., & Hwang, H. (2010). Regularized fuzzy clusterwise ridge regression. Advances in Data Analysis and Classification, 4, 35-51.
Hwang, H., & Takane, Y. (2010). Nonlinear generalized structured component analysis. Behaviormetrika, 37, 1-14.
2009
Hwang, H. (2009). Regularized generalized structured component analysis. Psychometrika, 74, 514-530.
Hwang, H., Tomiuk, M.A., & Takane, Y. (2009). Correspondence analysis, multiple correspondence analysis, and recent developments. In R. E. Millsap, & A. Maydeu-Olivares (Eds.). The SAGE Handbook of Quantitative Methods in Psychology (pp. 243-263). LA: Sage.
2008
Takane, Y., Hwang, H., & Abdi, H. (2008). Regularized multiple-set canonical correlation analysis. Psychometrika, 73, 753-775.
DeSarbo, S. W., Grewal, R., Hwang, H., & Wang, Q. (2008). The simultaneous identification of strategic groups and underlying dimensions for assessing market structure. Journal of Modelling in Management, 3, 220-248. (Awards for Excellence - Outstanding Paper)
Hwang, H. (2008). VisualGSCA 1.0 - A graphical user interface software program for generalized structured component analysis. In K. Shigemasu, A. Okada, T. Imaizumi, & T. Hoshino (Eds.). New Trends in Psychometrics (pp. 111 - 120). Tokyo: University Academic Press.
2007
Hwang, H., DeSarbo, S. W., & Takane, Y. (2007). Fuzzy clusterwise generalized structured component analysis. Psychometrika, 72, 181-198.
Hwang, H., Takane, Y., & Malhotra, N. (2007). Multilevel generalized structured component analysis. Behaviormetrika, 34, 95-109.
Takane, Y., & Hwang, H. (2007). Regularized linear and kernel redundancy analysis. Computational Statistics and Data Analysis, 52, 394-405.
Hwang, H., Takane, Y., & DeSarbo, S. W. (2007). Fuzzy clusterwise growth curve models via generalized estimating equations: An application to the antisocial behavior of children. Multivariate Behavioral Research, 42, 233-259.
2006
Hwang, H., Dillon, W. R., & Takane, Y. (2006). An extension of multiple correspondence analysis for identifying heterogeneous subgroups of respondents. Psychometrika, 71, 161-171.
Kim, Y., & Hwang, H. (2006). The effects of customer satisfaction on firm performance. Korean Management Review, 35, 1203-1221. (Best Research Award of the Korean Academic Society of Business Administration)
Takane, Y., Yanai, H., & Hwang, H. (2006). An improved method for generalized constrained canonical correlation analysis. Computational Statistics and Data Analysis, 50, 221-241.
Takane, Y., & Hwang, H. (2006). Regularized multiple correspondence analysis. In Greenacre, M. J., & Blasius, J. (Eds.). Multiple Correspondence Analysis and Related Methods (pp. 259-279). Chapman & Hall/CRC Press.
2005
Hwang, H., & Takane, Y. (2005). Estimation of growth curve models with structured error covariances by generalized estimating equations. Behaviormetrika, 32, 141-153.
Hwang, H., & Takane, Y. (2005). An extended multivariate random-effects growth curve model. Behaviormetrika, 32, 155-163.
Takane, Y., & Hwang, H. (2005). On a test of dimensionality in redundancy analysis. Psychometrika, 70, 1-11.
Takane, Y., & Hwang, H. (2005). An extended redundancy analysis and its applications to two practical examples. Computational Statistics and Data Analysis, 49, 785-808.
Hwang, H., Kim, Y., & Tomiuk, M. A. (2005). Latent growth curve modeling of the relationships among revenue, loyalty, and customer satisfaction by generalized structured component analysis. Asia Pacific Advances in Consumer Research, Vol. 6, 215-217.
Hwang, H., Yang, B., & Takane, Y. (2005). A simultaneous approach to constrained multiple correspondence analysis and cluster analysis for market segmentation. Asia Pacific Advances in Consumer Research, Vol. 6, 197-199.
2004
Hwang, H., & Takane, Y. (2004). Generalized structured component analysis. Psychometrika, 69, 81-99.
Hwang, H., & Takane, Y. (2004). A multivariate reduced-rank growth curve model with unbalanced data. Psychometrika, 69, 65-79.
2002
Hwang, H., & Takane, Y. (2002). Generalized constrained multiple correspondence analysis. Psychometrika, 67, 215-228.
Takane, Y., & Hwang, H. (2002). Generalized constrained canonical correlation analysis. Multivariate Behavioral Research, 37, 163-195.
Hwang, H. (2002). Analysis of categorical marketing data by generalized constrained multiple correspondence analysis. Korean Journal of Consumer and Advertising Psychology, 3, 53-62.
Hwang, H., & Takane, Y. (2002). Structural equation modeling by extended redundancy analysis. In S. Nishisato, Y. Baba, H. Bozdogan and K. Kanefuji (Eds.), Measurement and Multivariate Analysis (pp. 115-124). Tokyo: Springer Verlag.