• Asian Pacific Journal of Cancer Prevention
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• v.16 no.2
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• pp.647-652
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• 2015

Background: Lung cancer was one of the most common cancers in both men and women all over the world. In this study, we aimed to clarify who could survive after long term chemotherapy in patients with advanced non-small cell lung cancer (NSCLC). Methods: We enrolled 186 patients with stage IV NSCLC after long term chemotherapy from Jun 2006 to Nov 2014 diagnosed in Jiangsu Cancer Hospital. Multiple variables like age, gender, smoking, histology of adenocarcinoma and squamous-cell cancer, number of metastatic sites, metastatic sites (e.g. lung, brain, bone, liver and pleura), hemoglobin, lymphocyte rate (LYR), Change of LYR during multiple therapies, hypertension, diabetes, chronic bronchitis, treatments (e.g.radiotherapy and targeted therapy) were selected. For consideration of factors influencing survival and response for patients with advanced NSCLC, logistic regression analysis and Cox regression analysis were used in an attempt to develop a screening module for patients with elevated survival after long term chemotherapy become possible. Results: Of the total of 186 patients enrolled, 69 survived less than 1 year (short-term group), 45 one to two years, and 72 longer than 3 years (long-term group). For logistic regression analysis, the short-term group was taken as control group and the long-term group as the case group. We found that age, histology of adenocarcinoma, metastatic site (e.g. lung and liver), treatments (e.g. targeted therapy and radiotherapy), LYR, a decreasing tendency of LYR and chronic bronchitis were individually associated with overall survival by Cox regression analysis. A multivariable Cox regression model showed that metastatic site (e.g. lung and liver), histology of adenocarcinoma, treatments (e.g. targeted therapy and radiotherapy) and chronic bronchitis were associated with overall survival. Thus metastatic site (e.g. lung and liver) and chronic bronchitis may be important risk factors for patients with advanced NSCLC. Gender, metastatic site (e.g. lung and liver), LYR and the decreasing tendency of LYR were significantly associated with long-term survival in the individual-variable logistic regression model (P<0.05). On multivariate logistic regression analysis, gender, metastatic site (e.g. lung and liver) and the decreasing tendency of LYR associated with long-term survival. Conclusions: In conclusion, female patients with stage IV adenocarcinoma of NSCLC who had decreasing tendency of LYR during the course therapy and had accepted multiple therapies e.g. more than third-line chemotherapy, radiotherapy and/or targeted therapy might be expected to live longer.

• International Commerce and Information Review
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• v.11 no.2
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• pp.329-342
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• 2009

The purpose of this study was to identify the issues which how situational constraints of negotiation affect outcomes. To achieve the purpose of this research, a multiple regression model was set up to identify the relationships between situational constraints of negotiation and negotiation outcome on international trade contracts. To implement the study, empirical questionnaires were collected from Korean business men who have actually conducted international trade with foreign firms. Reliability analysis and factor analysis were used to assess the reliability and validity of research variables. and multiple regression analysis were used for testing the relationships between situational constraints of negotiation and negotiation outcome. From this study, following results were identified; i) situational constraints of negotiation effects on negotiation outcomes ii) arbitrary and continuous situations affect significantly positive on negotiation outcomes iii) submissive situations affect significantly negative effects on negotiation outcomes In conclusion, participant of negotiation and their managers try to promote negotiation situation toward to arbitrary and continuous situations if they have any availability.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.51 no.4
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• pp.269-273
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• 2006

Multiple linear regression analysis was conducted to interpretate the relationship between sesame grain yield and its components under early sowing cropping condition. The t test showed that stem length, number of capsules per plant, 1000 seeds weight and seed weight per plant gave significant contribution to sesame grain yield, therefore those variables were assumed to mostly influenced components to grain yield of sesame. In the stepwise regression analysis, the predicted equation for sesame grain yield per square meter (Y) was Y = -7.900 + 0.150X1 + 0.461X5 + 15.553X6 + 8.543X7. Meanwhile, F value showed that stem length, number of capsules per plant and seed weight per plant gave significant contribution to sesame grain yield, while 1000 seeds weight did not significantly show. Based on the results, it is reasonable to assume that high yield. potential of sesame under early sowing cropping condition would be obtained by selecting breeding lines with long stem length, number of capsules per plant, and seed weight per plant, which was different result at the late sowing cropping condition in which days to flowering and maturity were assumed to be more affected factors to the sesame grain yield.

• Industry Promotion Research
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• v.5 no.3
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• pp.45-51
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• 2020

This study analyzed the influence of investment and fostering support on gross regional product by utilizing big data using multiple regression analysis. Gross regional product (GRDP) is an index that intensively contains the production scale, expenditure level, income level, and industrial structure of each region, and is an important data used for regional economic analysis and national policy establishment. In order to properly carry out the country's major national tasks, it is necessary to accurately grasp the regional economy, and as a result, interest in regional gross domestic product is rapidly increasing. In particular, foreign investment has a significant impact on the economy of the host country, and many empirical analyzes are being conducted. In this study, correlation analysis and multiple regression analysis were conducted to examine the influence of foreign investment and domestic development support on gross regional product, and as a result, it was concluded that investment and support as a whole had a positive effect on gross regional product.

• Journal of Acupuncture Research
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• v.27 no.1
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• pp.11-20
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• 2010

Objectives : The study was performed to evaluate a traditional Korean Medicine content in drama "Daejanggeum". Methods : One hundred sixty-nine participants in Taiwan responded to the survey with 10 items, regarding components of success of drama "Daejanggeum". Principal component factor analysis and multiple regression analysis were performed to identify the possible factors to satisfaction with watching drama "Daejanggeum". Results : Factor analysis revealed that dramatic factor(44.8%), content factor(12.3%), and cultural factor(11.3%) were the most important factors to success of drama "Daejanggeum". Multiple regression analysis showed that dramatic factor(beta = .342), content factor(beta = .278), and cultural factor(beta = .131) were associated with the satisfaction with watching drama "Daejanggeum"($R^2$ = .394, with F = 32.280, p<.001). Conclusions : This study demonstrated that dramatic factor, content factor, and cultural factor are the most important factors associated with satisfaction with drama "Daejanggeum" in Taiwan. These findings suggest that a traditional Korean Medicine as a content factor would be very influential in enhancing the possibility of success of drama.

• Journal of Korean Society for Quality Management
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• v.35 no.4
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• pp.78-88
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• 2007

This paper is to investigate the relationship between international marketing and service quality, and the moderating effect of gender in that relationship. The data to make an empirical analysis were gathered from 269 workers in telecommunication sector. Multiple regression analysis revealed that (1) education was positively related with tangibility, reliability, responsiveness, empathy, assurance, and (2) internal communication was positively related with tangibility, reliability, responsiveness, assurance, and (3) delegation of authority was positively related with assurance. Hierarchical multiple regression analysis revealed that (4) compensation was more positively related with reliability in woman, and (5) employment security was more positively related with assurance in man.

• Proceedings of the Korean Society for Quality Management Conference
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• 2007.04a
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• pp.439-443
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• 2007

This paper is to investigate the relationship between international marketing and service quality, and the moderating effect of gender in that relationship. The data to make an empirical analysis were gathered from 269 workers in telecommunication sector. Multiple regression analysis revealed that (1) education was positively related with tangibility, reliability, responsiveness, empathy, assurance, and (2) internal communication was positively related with tangibility, reliability, responsiveness, assurance, and (3) delegation of authority was positively related with assurance. Hierarchical multiple regression analysis revealed that (4) compensation was more positively related with reliability in woman, and (5) employment security was more positively related with assurance in man.

• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.687-700
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• 2019

Purpose: The purpose of this study is to investigate the interaction effects between price determinants of artworks. We expand the methodology in art market by applying machine learning techniques to estimate the price of artworks and compare linear regression and machine learning in terms of prediction accuracy. Methods: Moderated regression analysis was performed to verify the interaction effects of artistic characteristics on price. The moderating effects were studied by confirming the significance level of the interaction terms of the derived regression equation. In order to derive price estimation model, we use multiple linear regression analysis, which is a parametric statistical technique, and k-nearest neighbor (kNN) regression, which is a nonparametric statistical technique in machine learning methods. Results: Mostly, the influences of the price determinants of art are different according to the auction types and the artist 's reputation. However, the auction type did not control the influence of the genre of the work on the price. As a result of the analysis, the kNN regression was superior to the linear regression analysis based on the prediction accuracy. Conclusion: It provides a theoretical basis for the complexity that exists between pricing determinant factors of artworks. In addition, the nonparametric models and machine learning techniques as well as existing parameter models are implemented to estimate the artworks' price.

• Tunnel and Underground Space
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• v.33 no.6
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• pp.594-609
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• 2023

TBM (Tunnel Boring Machine) method is gaining popularity in urban and underwater tunneling projects due to its ability to ensure excavation face stability and minimize environmental impact. Among the prominent models for predicting disc cutter life, the NTNU model uses the Cutter Life Index(CLI) as a key parameter, but the complexity of testing procedures and rarity of equipment make measurement challenging. In this study, CLI was predicted using multiple linear regression analysis and tree-based machine learning techniques, utilizing rock properties. Through literature review, a database including rock uniaxial compressive strength, Brazilian tensile strength, equivalent quartz content, and Cerchar abrasivity index was built, and derived variables were added. The multiple linear regression analysis selected input variables based on statistical significance and multicollinearity, while the machine learning prediction model chose variables based on their importance. Dividing the data into 80% for training and 20% for testing, a comparative analysis of the predictive performance was conducted, and XGBoost was identified as the optimal model. The validity of the multiple linear regression and XGBoost models derived in this study was confirmed by comparing their predictive performance with prior research.

• Journal of Korean Society on Water Environment
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• v.25 no.4
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• pp.580-588
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• 2009

In this study daily flow rates and delivered pollutant loads of Nakdong river basin are simulated with modified TANK model and minimum variance unbiased estimator. Based on the simulation results, flow duration curves, load duration curves, and delivery ratio duration curves have been established. Then GIS analysis is performed to obtain several hydrological geomorphic characteristics such as watershed area, stream length, watershed slope and runoff curve number. Finally, multiple regression analysis is carried out to estimate empirical equations for pollutants delivery ratio. The results show that there is positive relation between the flow rates and delivery ratios, and the proposed empirical formulas for delivery ratio can predict well river pollutant loads.