RESEARCH

Current Research Topics

Multivariate and Functional Data Analysis, Factor- and Component-based Structural Equation Modeling, Cluster Analysis, Data Integration, Statistical Learning, Neuroimaging & Genetic Data Analysis, Business Analytics

PUBLICATIONS

Book

Hwang, H., & Takane, Y. (2014). Generalized structured component analysis: A component-based approach to structural equation modeling. Boca Raton, FL: Chapman & Hall/CRC Press.

Winner of the Sugiyama Meiko Award (Publication Award) of the Behaviormetric Society of Japan

Journal Articles

Lee, S., Kim, Y., Choi, S., Hwang, H., & Park, T. (accepted). Pathway-based approach using hierarchical components of rare variants to analyze multiple phenotypes. BMC Bioinformatics.

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.

Hwang, H., Takane, Y., & Jung, K. (2017). Generalized structured component analysis with uniqueness terms for accommodating measurement error. Frontiers in Quantitative Psychology and Measurement, 8, Article 2137.

Ryoo, J. H., & Hwang, H. (2017). Model evaluation in generalized structured component analysis using confirmatory tetrad analysis. Frontiers in Quantitative Psychology and Measurement. 8, Article 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.

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., 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.

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.

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, Article 70, 1-17.

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.

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.

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.

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.

Hwang, H. (2009). Regularized generalized structured component analysis. Psychometrika, 74, 514-530.

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.

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.

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.

Takane, Y., Yanai, H., & Hwang, H. (2006). An improved method for generalized constrained canonical correlation analysis. Computational Statistics and Data Analysis, 50, 221-241.

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., & 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.

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.

Book Chapters & Conference Abstracts/Proceedings

Lee, J., Hwang, H., & Tran, A. (in press). Repositioning via abstraction. Advances in Consumer Research, Vol. 45.

Choi, J. Y., Yang, S., Tenenhaus, A., & Hwang, H. (in press). Three-way generalized structured component analysis. In M. Wiberg, S. Culpepper, R. Janssen, J. González, & D. Molenaar (Eds.). Quantitative Psychology: The 82nd Annual Meeting of the Psychometric Society, Zurich, Switzerland, 2017.

DeSarbo, W. S., Hwang, H., & Jedidi, K. (2016). Redundancy analysis. Wiley StatsRef: Statistics Reference Online (pp. 1–18). John Wiley & Sons.

Choi, S., Lee, S., Huh, I., Hwang, H., & Park, T. (2015). Competitive pathway analysis using structural equation models (CPA-SEM) for gene expression data. IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 1351-1358).

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.

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.

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.

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.

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.