Kyung Hee University · 医学
Professor Soeun Kim's research lab specializes in statistical methodology and biostatistical applications, with a focus on developing rigorous methods for handling incomplete data in regression models—particularly those involving interaction terms. The lab investigates advanced imputation strategies that account for complex data structures, such as interactions between continuous and binary predictors, under non-normal assumptions. It also contributes theoretical foundations for statistical inference in diagnostic test evaluation, especially in validating McNemar’s test under various dependence structures. The lab’s work bridges methodological innovation with practical applications in biomedical and health sciences.
Figures are computed from collected data and may differ slightly.
McNemar's test is often used in practice to compare the sensitivities and specificities for the evaluation of two diagnostic tests. For correct evaluation of accuracy, an intuitive recommendation is to test the diseased and the non-diseased groups separately so that the sensitivities can be compared among the diseased, and specificities can be compared among the healthy group of people. This paper provides a rigorous theoretical framework for this argument and study the validity of McNemar's tes
Imputation strategies are widely used in settings that involve inference with incomplete data. However, implementation of a particular approach always rests on assumptions, and subtle distinctions between methods can have an impact on subsequent analyses. In this research article, we are concerned with regression models in which the true underlying relationship includes interaction terms. We focus in particular on a linear model with one fully observed continuous predictor, a second partially ob
Epidermal development and differentiation are tightly controlled processes that culminate in the formation of the epidermal barrier. A critical regulator of different stages of epidermal development and differentiation is the transcription factor p63. More specifically, we previously demonstrated elsewhere that p63 is required for both the commitment to stratification and the commitment to terminal differentiation. We now demonstrate that DeltaNp63alpha, the predominantly expressed p63 isoform i
National Research Foundation and Ministry of Science and ICT of South Korea.
This paper investigates multiple imputation methods for regression models with interacting continuous and binary predictors when continuous variable may be missing. Usual implementations for parametric multiple imputation assume a multivariate normal structure for the variables, which is not satisfied for a binary variable nor its interaction with a continuous variable. To accommodate interactions, missing covariates are multiply imputed from conditional distribution in a manner consistent with
친환경에 대한 정부와 기업 그리고 소비자들의 다양한 실천이 이루어지고 있는 오늘날 소비자의 행동 의도에 영향을 미치는 요인들에 대한 파악은 무엇보다 중요하다. 본 연구에서는 고객의 친환경의식과 윤리의식이 친환경 외식업체 이용 의도에 어떠한 영향을 미치는지를 알아보고 특히 소비자의 의식에 많은 영향을 미치는 사회적 신뢰, 사회적 규범, 사회적 관계에 대해 분석하고자 하였다. 선행 연구의 고찰을 통해 연구모형 및 가설을 설정하였고, 346부의 자료를 Amos 및 process Macro를 통해 검증하였다. 분석결과 소비자의 친환 경 의식과 윤리의식은 친환경 외식업체 이용 의도에 정(+)의 영향을 미치고, 신뢰와 사회적 관계가 그사이를 매개하는 것으로 검증되었다. 이러한 분석결과를 통해 레스토랑 운영자및 실무자들에게 친환경 레스토랑 경영이 소비자의 이용 의도에 강력한 변수로 작용하고 있다는 것을 보여줌으로써 친환경 실천의 필요성을 시사하고 있다.
A fullerene-based reactive molecule (C60RM) was newly synthesized. Its chemical structure and phase behaviour were investigated using spectroscopic, scattering and microscopic techniques. Furthermore, the striped C60RM pattern was successfully fabricated in an elastically anisotropic cholesteric liquid crystal (CLC).
Based on multinational datasets from South Korea, the United States, and Norway, this study shows the potential of ML models, particularly the XGBoost model, in predicting adolescent substance use. These findings provide a solid basis for future research exploring additional influencing factors or developing targeted intervention strategies.
Air pollutants, such as particulate matter (PM) and diesel exhaust particles (DEP), are associated with respiratory diseases. Therefore, preventive and therapeutic strategies against PM-and DEP (PM<sub>10</sub>D)-induced respiratory diseases are needed. Herein, we evaluate the protective effects of a mixture of Lactiplantibacillus plantarum KC3 and Leonurus Japonicas Houtt (LJH) extract against airway inflammation associated with exposure to PM<sub>10</sub>D. To determine the anti-inflammatory e
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