Se-Kang Kim, Ph.D.
Picture
Se-Kang Kim, Ph.D.
Professor
Positions
- Professor
-
Pediatrics - Psychology
Baylor College of Medicine
Houston, US
Addresses
- 1102 Bates Ave Ste 940 (Office)
-
Houston, TX 77030
United States
Phone: (832) 822-3645
Se-Kang.Kim@bcm.edu
Education
- PhD from University of Minnesota
- 09/1999 - Twin Cities, Minnesota United States
- Statistics, Psychometrics
- MA from University of Toledo
- 09/1994 - Toledo, Ohio United States
- Psychology, Personality & Social Psychology
Professional Statement
Professor Se-Kang Kim participates in the development and application of sophisticated statistical methodologies. Present research interests include profile analysis for continuous data and correspondence analysis for categorical data. Correspondence analysis is intended to estimate association visually and quantitatively between any pair of categories included in a two-or multiway-contingency table. Profile analysis is intended to detect the central response patterns from a sample of various person response profiles. Both methods can detect novel, clinically significant features that are not readily captured by conventional statistical methods. His recent research focuses on the creation of innovative and efficient statistical methods and their application to clinical and medical domains. Professor Kim is eager to continue collaborating with research faculty in the Pediatric Psychology Division at Baylor College of Medicine to conduct data-driven, clinically relevant research.Selected Publications
- Kim, S.-K., McKay, D., Murphy, T.K., Bussing, R., McNamara, J.P, Goodman, W.K., & Storch, E.C. "Age moderated–anxiety mediation for multimodal treatment outcome among children with obsessive-compulsive disorder: An evaluation with correspondence analysis." J Affect Disord. 2021;282:766–775. Pubmed PMID: 33601717
- Kim, S.-K., McKay, D., Ehrenreich-May, J., Wood, J., & Storch, E.A. "Assessing treatment efficacy by examining relationships between age groups of children with autism spectrum disorder and clinical anxiety symptoms: Prediction by correspondence analysis." J Affect Disord. 2020;265(15):645–650. Pubmed PMID: 31787421
- Kim, S.-K., McKay, D., Cepeda, S.L., Schneider, S.C., Wood, J., & Storch, E.C "Assessment of improvement in anxiety severity for children with autism spectrum disorders: The matched correspondence analysis approach." J Psychiatr Res. 2022;145:175–181. Pubmed PMID: 34923358
- Kim, S.-K., & Annunziato, R.A. "Can eating disorder treatment also alleviate psychiatric comorbidity: Matched correspondence analysis?." Psychother Psychosom. 2020;89(2):125–127. Pubmed PMID: 31991442
- Kim, S.-K., & Annunziato, R.A "Estimating correlations among cardiovascular patients’ psychiatric and physical symptom indicators: The biplot in correspondence analysis approach." Int J Methods Psychiatr Res. 2018; Pubmed PMID: 29498151
- Kim, S.-K., McKay, D., & Tolin, D.F. "Examining the generality and specificity of gender moderation in obsessive compulsive beliefs: stacked prediction by correspondence analysis." Br J Clin Psychol. 2022;61:613–628. Pubmed PMID: 34468041
- Kim, S.-K. "Factorization of person response profiles to identify summative profiles carrying central response patterns." Psychol Methods. 2023; Pubmed PMID: 36972078
- Kim, S.-K., & Frisby, C.L. "Gaining from discretization of continuous data: The correspondence analysis biplot approach." Behav Res Methods. 2019;51(2):589–601. Pubmed PMID: 30406507
- Kim, S.-K., Annunziato, R.A., & Olatunji, B.O. "Profile analysis of the effects of treatment on change in eating disorder indicators." Int J Methods Psychiatr Res. 2017; Pubmed PMID: 29168266
- Kim, S.-K. "Test treatment effect differences in repeatedly measured symptoms with binary values: The matched correspondence analysis approach." Behav Res Methods. 2020;52:1480-1490. Pubmed PMID: 32077082
- Kim, S.-K., McKay, D., Goodman, W.K., Small, B.J., McNamara, J.P., & Murphy, T.K., & Storch, E.A. "Understanding anxiety and symptom impact mediators explaining cognitive-behavior therapy and pharmacotherapy response in childhood obsessive-compulsive disorder." J Psychopathol Behav Assess. 2020;42:739–750.
- Kim, S.-K., & Grochowalski, J.H "Exploratory visual inspection of category associations and correlation estimation in multidimensional subspaces." J Classif. 2019;36(2):177–199.
- Kim, S.-K., & Kim, D. "A tool extracting summative profiles from person score profiles: profile analysis via principal component analysis (PAPCA)." Methodology. 2017;13:71–81.
- Kim, S.-K., McKay, D., Taylor, S., Tolin, D.F, Olatunji, B.O, Timpano, K.R, & Abramowitz, J.S. "The Structure of obsessive compulsive symptoms and beliefs: A correspondence and biplot analysis.." J Anxiety Disord. 2016;38:79–87. Pubmed PMID: 26851748
- Kim, S.-K. "Identifying between-person and within-person factors to enhance understanding observed score profiles." Br J Math Stat Psychol. 2013;(66):435–451. Pubmed PMID: 23020157
Skills
- Correspondence Analysis
- Correspondence analysis is a statistical method used to examine the relationship between categories in a two- or multi-way contingency table. It allows for the estimation of associations between categories both visually and numerically. The biplot paradigm is employed to project categories onto a two-dimensional plane for a visual examination of category associations. In order to provide numerical estimates of visually observed associations, correlations are calculated based on the category coordinates in the biplot plane.
- Profile Analysis
- Profile analysis is to detect the most predominant response patterns among a set of individual profiles of observed responses. The profile analytic method has been employed to evaluate patients in terms of their symptom improvement and deterioration.
Languages
Korean
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