• Journal of dental hygiene science
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• v.2 no.2
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• pp.63-67
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• 2002

The purpose of this study was to develop more effective dental health education program and to reduce the occurrence of dental diseases among industrial men-workers in Korea. The questionaire and dental examination were given to 782 industrial men-workers who visited Asan Medical Center for the purpose of health examinations in 2000. The obtained results were as follows; 1. According to the results of logistic regression analysis, both ages (especially under 30's: P=0.027) and monthly incomes (especially under 1,000,000 won: P=0.000) show negative relationships with the occurrence of dental caries. 2. As the results of logistic regression analysis, ages shows positive relationship and monthly incomes shows negative relationship (only under 1,000,000 won: P=0.059) with the occurrence of missing teeth. 3. According to the results of logistic regression analysis of periodontal disease, the model shows no significance (P=0.117). 4. As the results of logistic regression analysis, both monthly incomes and ages show positive relationships with the occurrence of abrasion.

• The Korean Journal of Applied Statistics
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• v.1 no.2
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• pp.45-60
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• 1987

Deciding whether a certain cancer patient is suffering from a bone marrow metastasis is quite essential to clinicians. To find a set of explanatory variables of the bone marrow metastasis, we employed the logistic regression analysis on 60 cancer patients with bone marrow metastasis (the case group) and 41 cancer patients without bone marrow metastasis (the control group). These data shown in Append were collected retrospectively from the record of Severance Hospital of Yonsei University College of Medicine from January, 1977 to December, 1985. We could establish a set of decision rules of the bone marrow metastasis specially designed for clinicians based on the explanatory variables of the best fitting logistic regression equation. We also compute the specifity and the sensistivity of our decision rules.

• Journal of Korean Society for Quality Management
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• v.46 no.3
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• pp.453-464
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• 2018

Purpose: The purpose of this study is to propose a solution to the case where $V_{50}$ calculation is impossible in the process of bulletproof test. Methods: In this study, we proposed a $V_{50}$ estimation method using logistic regression analysis. Six scenarios were applied by combining the homogeneity of the sample and the speed range. Then, 1,000 simulations were performed per scenario and six assumptions reflecting the reality were applied. Results: The result of the study, it was confirmed that there was no statistical difference between the $V_{50}$ value calculated by the conventional method and the $V_{50}$ value calculated by the improvement method. Therefore, in situations where $V_{50}$ can not be calculated, it is reasonable to use logistic regression analysis. Conclusion: This study develops a methodology that is easy to use and reliable by using statistical model based on actual data.

• Journal of the Korean earth science society
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• v.31 no.5
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• pp.454-464
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• 2010

A probability prediction model for tropical cyclone (TC) genesis in the Northwestern Pacific area was developed using the logistic regression method. Total five predictors were used in this model: the lower-level relative vorticity, vertical wind shear, mid-level relative humidity, upper-level equivalent potential temperature, and sea surface temperature (SST). The values for four predictors except for SST were obtained from difference of spatial-averaged value between May and January, and the time average of Ni$\tilde{n}$o-3.4 index from February to April was used to see the SST effect. As a result of prediction for the TC genesis frequency from June to December during 1951 to 2007, the model was capable of predicting that 21 (22) years had higher (lower) frequency than the normal year. The analysis of real data indicated that the number of year with the higher (lower) frequency of TC genesis was 28 (29). The overall predictability was about 75%, and the model reliability was also verified statistically through the cross validation analysis method.

• Journal of Oriental Neuropsychiatry
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• v.16 no.2
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• pp.65-72
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• 2005

Objectives : This study is for discovering the clinical Features of the sleep in ordinary symptoms based on the Sasang Constitution. The result of this study could be helpful to understand and to identify the patients as Soyangin in contrast with the other constitutions -Soeumin, Taeumin and Taeyangin. Methods : There were 1,229 patients(700 female), who answered the questionnaire about their ordinary sleeping patterns. They had been diagnosed, including their clinical Sasang Constitution, by the Sasang Constitution specialist at Bundang Oriental Hospital of Dongguk University. By applying the binary logistic regression analysis, we can measure the characteristics and the influence of ordinary sleeping patterns to the dependent variable(Sasang Constitution). Results : As a result of the binary logistic analysis on the observed questionnaire, we found the characteristics of the ordinary sleeping patterns on Soyangin in contrast with the other constitutions. Firstly, Soyangin has a tendency that he wouldn't dreams more, when he sleeps in contrast with the others. Secondly, Soyangin has a tendency that he wouldn't sleep longer than 6-7hours. Thirthly, Soyangin has a tendency that he will sleep well in contrast with the others. Conclusion : This study will be used to identify patients as Soyangin in contrast with the others-Soemin, Taeumin and Taeyangin.

• Journal of Applied Reliability
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• v.18 no.1
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• pp.1-7
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• 2018

Purpose: Maintaining appropriate operational availability (Ao) is a key element of combat victory, but estimates vary according to estimation methods. The purpose of this study is to improve the accuracy of estimating operational availability by tracing the changes of the weapon system's failure rate, repair rate, and the level of logistic support. Methods: In order to track the change in the operating availability, the MDT (mean down time) is modeled by adding the repair time and the ALDT (administration and logistic delay time) to the service time. Results: Using the field data of the weapon system A operated by the ROKAF, the failure rate follows a non-homogeneous Poisson process that changes with time, and it is modeled considering the changing repair rate and the logistic support time. Conclusion: The accuracy of the analytical results was verified by comparing the actual operating data with the estimated availability. The results of this study can be used to track and evaluate the availability in a realistic situation where the failure rate and maintenance rate continuously change in operating environment.

• Journal of the Korean Data and Information Science Society
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• v.22 no.5
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• pp.931-940
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• 2011

Classification is to generate a rule of classifying objects into several categories based on the learning sample. Good classification model should classify new objects with low misclassification error. Many types of classification methods have been developed including logistic regression, discriminant analysis and tree. This paper presents a new classification method using penalized partial least squares. Penalized partial least squares can make the model more robust and remedy multicollinearity problem. This paper compares the proposed method with logistic regression and PCA based discriminant analysis by some real and artificial data. It is concluded that the new method has better power as compared with other methods.

• Journal of Korean Society of Forest Science
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• v.99 no.2
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• pp.163-171
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• 2010

Forest fires have potentials to change the structure and function of forest ecosystems and significantly influence on atmosphere and biogeochemical cycles. Forest fire also affects the quality of public benefits such as carbon sequestration, soil fertility, grazing value, biodiversity, or tourism. The prediction of fire occurrence and its spread is critical to the forest managers for allocating resources and developing the forest fire danger rating system. Most of fires were human-caused fires in Korea, but meteorological factors are also big contributors to fire behaviors and its spread. Thus, meteorological factors as well as social factors were considered in the fire danger rating systems. A total of 298 forest fires occurred during the fall season from 2002 to 2006 in South Korea were considered for developing a logistic model of forest fire occurrence. The results of statistical analysis show that only effective humidity and temperature significantly affected the logistic models (p<0.05). The results of ROC curve analysis showed that the probability of randomly selected fires ranges from 0.739 to 0.876, which represent a relatively high accuracy of the developed model. These findings would be necessary for the policy makers in South Korea for the prevention of forest fires.

• The Korean Journal of Applied Statistics
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• v.32 no.5
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• pp.653-669
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• 2019

The development of new media has gradually decreased the use of newspapers, which had previously occupied the largest share of media. Subscriptions have declined gradually and fell to 14 percent in 2016. This study explores the effects of Newspaper reader's characteristics on regular newspaper subscriptions. The data used for analysis was provided by the Korean Press Foundation and Media Audience Awareness Survey Data in 2016 and 2017. We considered gender, age, education, income, number of days of reading, reading time and amount of reading as the characteristics of the reader. Multiple logistic regression was fitted and interpreted to see what characteristics affect regular subscription.

• Journal of Applied Reliability
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• v.16 no.1
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• pp.48-55
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• 2016

Purpose: The purpose of this study is to identify the object-oriented metrics which have strong impact on the reliability and fault-proneness of software products. The reliability and fault-proneness of software product is closely related to the design properties of class diagrams such as coupling between objects and depth of inheritance tree. Methods: This study has empirically validated the object-oriented metrics to determine which metrics are the best to predict fault-proneness. We have tested the metrics using logistic regressions and artificial neural networks. The results are then compared and validated by ROC curves. Results: The artificial neural network models show better results in sensitivity, specificity and correctness than logistic regression models. Among object-oriented metrics, several metrics can estimate the fault-proneness better. The metrics are CBO (coupling between objects), DIT (depth of inheritance), LCOM (lack of cohesive methods), RFC (response for class). In addition to the object-oriented metrics, LOC (lines of code) metric has also proven to be a good factor for determining fault-proneness of software products. Conclusion: In order to develop fault-free and reliable software products on time and within budget, assuring quality of initial phases of software development processes is crucial. Since object-oriented metrics can be measured in the early phases, it is important to make sure the key metrics of software design as good as possible.