• Proceedings of the Korean Society of Food Hygiene and Safety Conference
• /
• 1997.06b
• /
• pp.91-91
• /
• 1997

• Clinics in Shoulder and Elbow
• /
• v.16 no.1
• /
• pp.63-72
• /
• 2013

In medical research, multivariate analysis, especially multiple regression analysis, is used to analyze the influence of multiple variables on the result. Multiple regression analysis should include variables in the model and the problem of multi-collinearity as there are many variables as well as the basic assumption of regression analysis. The multiple regression model is expressed as the coefficient of determination, $R^2$ and the influence of independent variables on result as a regression coefficient, ${\beta}$. Multiple regression analysis can be divided into multiple linear regression analysis, multiple logistic regression analysis, and Cox regression analysis according to the type of dependent variables (continuous variable, categorical variable (binary logit), and state variable, respectively), and the influence of variables on the result is evaluated by regression coefficient${\beta}$, odds ratio, and hazard ratio, respectively. The knowledge of multivariate analysis enables clinicians to analyze the result accurately and to design the further research efficiently.

• Proceedings of the KSME Conference
• /
• 2007.05a
• /
• pp.250-255
• /
• 2007

Steam generator tubes play an important role in safety because they constitute one of the primary barriers between the radioactive and non-radioactive sides of the nuclear power plant. For this reason, the integrity of the tubes is essential in minimizing the leakage possibility of radioactive water. The integrity of the tubes is evaluated based on NDE (non-destructive evaluation) inspection results. Especially ECT (eddy current test) method is usually used for detecting the flaws in steam generator tubes. However, detection capacity of the NDE is not perfect and all of the "real flaws" which actually existing in steam generator tunes is not known by NDE results. Therefore reliability of NDE system is one of the essential parts in assessing the integrity of steam generators. In this study POD (probability of detection) of ECT system for ODSCC in steam generator tubes is evaluated using multivariate logistic regression. The cracked tube specimens are made using the withdrawn steam generator tubes. Therefore the cracks are not artificial but real. Using the multivariate logistic regression method, continuous POD surfaces are evaluated from hit (detection) and miss (no detection) binary data obtained from destructive and non-destructive evaluation of the cracked tubes. Length and depth of cracks are considered in multivariate logistic regression and their effects on detection capacity are evaluated.

• The Journal of the Korea Contents Association
• /
• v.20 no.7
• /
• pp.118-126
• /
• 2020

The purpose of the study is to analyze the relationship between the warning picture on a cigarette pack and non-smoking attempt, which is expected to contribute to the negative perception of smoking as a research subject about smoking adolescents. An online survey data of the Youth Health Behavior in 2018 has been used, and 3,722 adolescents who are currently smokers were selected for the study. For the measurement of variables, demographic sociology, health-related, and smoking-related factors have been revised, and multivariate binomial logistic regression analysis has been performed. The perception rate of cigarette warning pictures among adolescents who smoke currently is 84.7%, and among them, the attempt rate to quit smoking is 72.8%. As a result of the multivariate binomial logistic regression analysis, there is a meaningful relationship between adolescent smokers' attempts to quit smoking and whether they perceived cigarette pack warning pictures, and school grade year, academic performance, stress perception, and ease of purchasing cigarettes have been also expressed as meaningful variables. To be based on the result, it is necessary to manufacture to design a cigarette pack warning picture that can be easily recognized by smoking adolescents in the future.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2006.06a
• /
• pp.195-202
• /
• 2006

본 연구에서는 보다 효과적인 기업부도예측을 위하여, 동계적 방법과 인공지능 방법을 결합한 통합모형을 제시하였다. 이를 위하여 통계적인 모형 중에서 가장 널리 활용되고 있는 다변량 판별분석, 로지스틱 회귀분석과 인공 지능적인 방법으로서 최근 널리 사용되고 있는 인공신경망, 규칙유도기법, 베이지안 망의 5가지 방법론을 통합한 Voting with Performance & Weights from ANN(WP-ANN) 통합모형을 제시하였다. 실험결과, 본 연구에서 제안한 WP-ANN 통합모형은 다변량 판별분석, 로지스탁 회귀분석, 인공신경망, 규칙유도기법, 베이지안 망 등의 단일모형과 비교한 결과 가장 예측정확성이 유수한 것으로 나타났다. 따라서 본 연구를 통해 기업부도예측에 있어서 WP-ANN 통합모형이 기존의 모형들에 비해 우수한 예측정확성을 나타냄을 알 수 있었다.

• Proceedings of the Korea Society for Industrial Systems Conference
• /
• 2009.05a
• /
• pp.114-119
• /
• 2009

본 논문에서는 수량화 방법과 AHP(Analytic Hierarchy Process) 기법을 사용하여 산사태 발생에 대한 통계적 예측모형을 구축하는데 목적이 있다. 수량화(Quantification) 방법은 질적변수에 수량을 부여하는 통계적 방법으로, 기 조사된 자료에 기반하여 분석을 수행하는 방법이다. 본 논문에서는 서구의 다변량분석 기법인 정준상관분석의 결과를 토대로 수량화 과정을 구체적으로 제안한다. 데이터에 기반한 수량화 방법과는 달리 AHP(Analytic Hierarchy Process) 기법은 일종의 다기준 의사결정을 위해 사용되는 기법으로, 설문자료에 기반한 분석법이다. 실제자료에 대한 분석으로 산사태 발생여부를 측정한 자료(한국지질자원연구원 제공)와 전문가 설문을 통해 수집된 자료를 이용하였다. 이들 자료에 대해 수량화 분석과 AHP분석을 통해 산사태 발생여부를 예측할 수 있는 두 종류의 평가표와 함께 로지스틱 회귀를 통한 통계적 예측모형을 개발하였으며, 두 모형간의 성능비교와 안정성 평가를 수행하였다.

• Journal of Digital Convergence
• /
• v.18 no.9
• /
• pp.297-305
• /
• 2020

The purpose of this study was to identify the factors associated with subjective age among community-dwelling older adults in South Korea. Cross-sectional analyses were performed on 8,040 older adults aged 65 years and over from the 2017 National Survey of Older Koreans. We used univariable analysis and multivariable analysis by the logistic regression test. The significant factors associated with subjective age in older adults were gender, education level, living arrangements, limitation of instrumental activities of daily living, number of chronic diseases, perceived health status, depression, and current economic activity. Based on the results of this study, nursing intervention will be needed to lower subjective age. This study may contribute to the older adults to have a healthy and successful old age.

• The Korean Journal of Applied Statistics
• /
• v.26 no.2
• /
• pp.223-236
• /
• 2013

Various statistical classification methods to predict election to the Major League Baseball hall of fame of are implemented and their accuracies are compared. Seventeen independent variables are selected from the data of candidates eligible for the hall of fame and well-known classification methods such as discriminant analysis and logistic regression as well as the recently proposed Mahalanobis-Taguchi system(MTS). The MTS showed a better performance than the others in classification accuracy because it is especially efficient in cases where multivariate data does not constitute directionally geographical groups according to attributes.

• Journal of Korean society of Dental Hygiene
• /
• v.21 no.5
• /
• pp.535-543
• /
• 2021

Objectives: This study investigated the relationship between the Korean healthy eating index (KHEI) and periodontal disease in the Korean adult population. Methods: The data used in the analyses were obtained from the seventh Korean National Health and Nutrition Examination Survey (2016-2018). Data were analyzed by chi-square tests and t-test. Multiple regression analysis was also performed to assess the association between KHEI and periodontal disease. Statistical significance was set at p<0.05. Results: Multiple logistic regression analysis adjusted for socioeconomic variables showed that medical and health behavior variables were significantly related to the KHEI 1 (<63.7, odds ratio [OR]: 1.23, 95% confidence interval [CI]: 1.03-1.46), KHEI 2 (63.7-79.9, OR: 1.14, 95% CI: 0.97-1.34), and risk for periodontal disease. Conclusions: The results showed a significant association between the KHEI and periodontal disease in the Korean adult population.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.22 no.10
• /
• pp.1277-1286
• /
• 2018

In this paper, we provide flexible scalability of computing resources in cloud environment and Apache Hadoop based cloud environment for analysis of public medical information big data. In fact, it includes the ability to quickly and flexibly extend storage, memory, and other resources in a situation where log data accumulates or grows over time. In addition, when real-time analysis of accumulated unstructured log data is required, the system adopts Hadoop-based analysis module to overcome the processing limit of existing analysis tools. Therefore, it provides a function to perform parallel distributed processing of a large amount of log data quickly and reliably. Perform frequency analysis and chi-square test for big data analysis. In addition, multivariate logistic regression analysis of significance level 0.05 and multivariate logistic regression analysis of meaningful variables (p<0.05) were performed. Multivariate logistic regression analysis was performed for each model 3.