• Proceedings of the Korean Statistical Society Conference
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• 2003.10a
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• pp.179-182
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• 2003

This study describes a new graphical method for assessing and characterizing effect modification by a matching covariate in matched case-control studies. This method to understand effect modification is based on a semiparametric model using a varying coefficient model. The method allows for nonparametric relationships between effect modification and other covariates, or can be useful in suggesting parametric models. This method can be applied to examining effect modification by any ordered categorical or continuous covariates for which cases have been matched with controls. The method applies to effect modification when causality might be reasonably assumed. An example from veterinary medicine is used to demonstrate our approach. The simulation results show that this method, when based on linear, quadratic and nonparametric effect modification, can be more powerful than both a parametric multiplicative model fit and a fully nonparametric generalized additive model fit.

• Communications for Statistical Applications and Methods
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• v.16 no.4
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• pp.713-722
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• 2009

The estimation of odds ratio and corresponding confidence intervals for case-control data have been done by traditional generalized linear models which assumed that the logarithm of odds ratio is linearly related to risk factors. We adapt a lower-dimensional approximation of Gu and Kim (2002) to provide a faster computation in nonparametric method for the estimation of odds ratio by allowing flexibility of the estimating function and its Bayesian confidence interval under the Bayes model for the lower-dimensional approximations. Simulation studies showed that taking larger samples with the lower-dimensional approximations help to improve the smoothing spline estimates of odds ratio in this settings. The proposed method can be used to analyze case-control data in medical studies.

• Journal of Pharmacopuncture
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• v.26 no.1
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• pp.67-76
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• 2023

Objectives: Medical services are closely related to individual health and welfare, and health status in childhood or adolescence is widely recognized to be related to many socioeconomic outcomes. Therefore, providing appropriate medical services in childhood and adolescence is important. We aimed to investigate the determinants of traditional Korean medical services (TKMS) usage by children aged < 19 years. The focus was on the role of their parents' experiences with TKMS in determining TKMS use by children. Methods: Using a representative sample in South Korea, we conducted a regression analysis to assess how parents' experience with TKMS affects the probability of their children using TKMS. Results: We found parents' experience with TKMS to have a significantly positive effect on the probability of TKMS use by children and parents' biological information, such as age and sex, to affect the probability of TKMS use. Specifically, parents' experiences with TKMS generally increased the probability of children using TKMS by approximately 20%. Conclusion: This study's results suggest that considering parents' opinions and providing them the opportunity to participate in programs that enhance young children's use of TKMS may be effective.

• Journal of Animal Science and Technology
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• v.45 no.5
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• pp.711-724
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• 2003

Some growth curve models were used to fit individual growth of 1,083 Hanwoo cows born from 1970 to 2001 in Daekwanryeong branch, National Livestock Research Institute(NLRI). The effects of year-season of birth and age of dam were analyzed. In analysis of variance for growth curve parameters, the effects of birth year-season were significant for mature weight(A), growth ratio(b) and maturing rate(k)(P〈.01). The effects of age of dam were significant for growth ratio(b) but not significant for mature weight(A) and maturing rate(k). The linear term of the covariate of age at the final weights was significant for the A(P〈.01) and k(P〈.01) of Gompertz model, von Bertalanffy model and Logistic model. For the growth curve parameters fitted on individual data using Gompertz model, von Bertalanffy model and Logistic model, resulting the linear contrasts(fall-spring), Least square means of A in three nonlinear models were higher cows born at fall and A of Logistic model was significant(P〈.05) between the seasons. According to the results of the least square means of growth curve parameters by age of dam, least square means of mature weight(A) in Gompertz model was largest in 6 year and smallest estimating for 3 and 8 years of age of dam. The growth ratio(b) was largest in 2 year of age of dam and smallest estimating in 8 year. The A and k were not different by age of dam(p〉.05), On the other hand, the b was different by age of dam(p〈.01). The estimate of A in von Bertalanffy model was largest in 6 year and smallest in 8 and 9 years of age of dam. The b was largest in 2 year and tend to decline as age of dam increased. The A and k were not different by age of dam(p〉.05), On the other hand, the b was highly significant by age of dam(p〈.01).

• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.13-20
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• 2022

It's proposed and analyzed ML(Machine Learning) models to predict vehicle FC(Fuel Consumption) in real-time. The test driving was done for a car to measure vehicle speed, acceleration, road gradient and FC for training dataset. The various ML models were trained with feature data of speed, acceleration and road-gradient for target FC. There are two kind of ML models and one is regression type of linear regression and k-nearest neighbors regression and the other is classification type of k-nearest neighbors classifier, logistic regression, decision tree, random forest and gradient boosting in the study. The prediction accuracy is low in range of 0.5 ~ 0.6 for real-time FC and the classification type is more accurate than the regression ones. The prediction error for total FC has very low value of about 0.2 ~ 2.0% and regression models are more accurate than classification ones. It's for the coefficient of determination (R²) of accuracy score distributing predicted values along mean of targets as the coefficient decreases. Therefore regression models are good for total FC and classification ones are proper for real-time FC prediction.

• Food Science of Animal Resources
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• v.43 no.1
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• pp.113-123
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• 2023

This study investigated the predictability of cooking loss of pork loin through relatively easy and quick measurable quality properties. The pH, color, moisture, protein content, and cooking loss of 100 pork loins were measured. The explanatory variables included in all linear regression models with an adjust-r² value of ≥0.5 were pH and the protein content. In the linear regression model predicting cooking loss, the highest adjust-r² value was 0.7, with pH, CIE L^*, CIE b^*, moisture, and protein content as the explanatory variables. In 30 pork loins, electrical conductivity was additionally measured, and as a result of linear regression analysis for predicting cooking loss, the highest adjust-r² value was 0.646 with electrical conductivity measured at 40 Hz, with pH and color as the explanatory variables. Ordinal logistic regression analysis was performed to predict the three grades (low, middle, and high) of loin cooking loss using pH, color, and 40 Hz electrical conductivity as the explanatory variables, and the percent concordance was 93.8%. In conclusion, the addition of electrical conductivity as an explanatory variable did not increase the prediction accuracy of the linear regression model for predicting cooking loss; however, it was demonstrated that it is possible to predict and classify the cooking loss grade of pork loin through quality properties that can be measured quickly and easily.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.53 no.1
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• pp.50-56
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• 2020

Determination of the precise size at sexual maturity is very important for science-based stock assessment and fisheries resource management. In this study, two different models, (1) a visual method and (2) a gonadosomatic index (GSI) method, were employed to estimate length at sexual maturity of the small yellow croaker Larimichthys polyactis in the Yellow Sea of Korea. The visual method is a common qualitative method using visual gonadal identification. Conversely, the GSI method is a quantitative method using the GSI, which can be easily and precisely collected. We compared results from these methods to determine the best approach, and to examine the practicality of the GSI method. Logistic regression of the maturity ogive was conducted using a general linear model (GLM) with the R statistics program. Also, the bootstrapped 95% confidence intervals of all estimates were calculated. The best-fit model was the visual method (R_Mc²=0.805, AUC=0.989, L₅₀=15.1). Among models using the GSI method, the model computing GSI_ref=0.94 was the best-fit model (R_Mc²=0.792, AUC=0.989, L₅₀=15.2). There was no significant difference between the two models, evidencing the effectiveness and accuracy of the GSI method.

• Asian-Australasian Journal of Animal Sciences
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• v.33 no.8
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• pp.1360-1368
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• 2020

Objective: The aim of our study was to determine the associations of heifer reproductive performance with survival up to the first calving, first-lactation milk yield, and the probability of being culled within 50 days after first calving. Methods: Data from 33 large Holstein-Friesian commercial dairy herds were gathered from the official milk recording database in Hungary. The data of heifers first inseminated between January 1, 2011 and December 31, 2014 were analyzed retrospectively, using Cox proportional hazards models, competing risks models, multivariate linear and logistic mixed-effects models. Results: Heifers (n = 35,128) with younger age at conception were more likely to remain in the herd until calving, and each additional month in age at conception increased culling risk by 5.1%. Season of birth was related to first-lactation milk yield (MY1; n = 19,931), with cows born in autumn having the highest milk production (p<0.001). The highest MY1 was achieved by heifers that first calved between 22.00 and 25.99 months of age. Heifers that calved in autumn had the highest MY1, whereas calving in summer was related to the lowest milk production (p<0.001). The risk of culling within 50 days in milk in first lactation (n = 21,225) increased along with first calving age, e.g. heifers that first calved after 30 months of age were 5.52-times more likely to be culled compared to heifers that calved before 22 months of age (p<0.001). Calving difficulty was related to higher culling risk in early lactation (p<0.001). Heifers that required caesarean section were 24.01-times more likely to leave the herd within 50 days after first calving compared to heifers that needed no assistance (p<0.001). Conclusion: Reproductive performance of replacement heifers is closely linked to longevity and milk production in dairy herds.

• Journal of Nutrition and Health
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• v.55 no.2
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• pp.309-320
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• 2022

Purpose: This study aimed to investigate the association between steamed food intake and risk of metabolic syndrome (MetS) in Korean females. Methods: Using Ansan/Ansung data of Korean Genome and Epidemiology Study, general characteristics, nutritional intake and biochemical and anthropometric markers of a total of 4,056 females aged 40 to 69 years were analyzed. MetS was defined following National Cholesterol Education Program Adult Treatment Panel III with some minor modifications. Logistic regression models were established to present the association between steamed food intake and the risk of MetS. Levels of food and nutrient intake by the frequency of steamed food intake and MetS phenotype were analyzed using general linear models. Results: A total of 38.4% of females had MetS. Among them, 24.9% of females with MetS had steamed food more than 1-3 times per week, which reduced the risk for MetS by about 25% (95% confidence interval [CI], 0.650-0.865). However, such association was not evident when various lifestyle factors were considered in statistical models. In rural residents, the benefit of having more steamed food was observed (adjusted odds ratio: 0.747; 95% CI, 0.583-0.958). The frequency of steamed food intake was associated with various food and nutritional intakes. However, trends in those did not differ by MetS phenotype. Conclusion: Having steamed food more than 1-3 times per week may reduce the risk of MetS compared to those who had less steamed food in Korean females. This protective effect of steamed food intake may differ by lifestyle and environmental factors. Although a clear difference in food and nutritional intake was not observed in this study, steaming could be an effective cooking method for a healthy diet for disease prevention and management.

• Journal of Practical Engineering Education
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• v.16 no.3_spc
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• pp.291-296
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• 2024

This study analyzed various machine learning models that predict employment outcomes after vocational training using pre-assessment data of disabled vocational trainees. The study selected and utilized the most appropriate machine learning models based on a data set containing various personal characteristics, including trainees' gender, age, and type of disability. Through this analysis, the goal is to improve the employment rate and job satisfaction of disabled trainees using only pre-assessment data. As a result, it presents a universal approach that can be applied not only to people with disabilities, but also to vocational trainees from a variety of backgrounds. This is expected to make an important contribution to the development and implementation of tailored vocational training programs, ultimately helping to achieve better employment outcomes and job satisfaction.