• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.1
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• pp.26-37
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• 2017

The study is to develop safety performance functions(SPFs) for urban intersections using random effects Tobit regression model and to analyze correlations between crashes and factors. Also fixed effects Tobit regression model was estimated to compare and analyze model validation with random effects model. As a result, AADT, speed limits, number of lanes, land usage, exclusive right turn lanes and front traffic signal were found to be significant. For comparing statistical significance between random and fixed effects model, random effects Tobit regression model of total crash rate could be better statistical significance with $R^2_p$ : 0.418, log-likelihood at convergence: -3210.103, ${\rho}^2$: 0.056, MAD: 19.533, MAPE: 75.725, RMSE: 26.886 comparing with $R^2_p$ : 0.298, log-likelihood at convergence: -3276.138, ${\rho}^2$: 0.037, MAD: 20.725, MAPE: 82.473, RMSE: 27.267 for the fixed model. Also random effects Tobit regression model of injury crash rate has similar results of model statistical significant with random effects Tobit regression model.

• Journal of the Korean Society of Safety
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• v.29 no.5
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• pp.154-159
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• 2014

This study deals with the pedestrian accidents of intersections in case of Cheongju. The objective is to develop the pedestrian accident models using Tobit regression model. In pursuing the above, the pedestrian accident data from 2007 to 2011 were collected from TAAS data set of Road Traffic Authority. To analyze the accident, Poisson, negative binomial and Tobit regression models were utilized in this study. The dependent variable were the number of accident by intersection. Independent variables are traffic volume, intersection geometric structure and the transportation facility. The main results were as follows. First, Tobit model was judged to be more appropriate model than other models. Also, these models were analyzed to be statistically significant. Second, such the main variables related to accidents as traffic volume, pedestrian volume, number of traffic island, crossing length and the pedestrian countdown signal systems were adopted in the above model.

• International Journal of Highway Engineering
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• v.16 no.3
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• pp.101-107
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• 2014

PURPOSES : This study deals with the pedestrian accidents in case of Cheongju. The goals are to develop the pedestrian accident model. METHODS : To analyze the accident, count data models, truncated count data models and Tobit regression models are utilized in this study. The dependent variable is the number of accident. Independent variables are traffic volume, intersection geometric structure and the transportation facility. RESULTS : The main results are as follows. First, Tobit model was judged to be more appropriate model than other models. Also, these models were analyzed to be statistically significant. Second, such the main variables related to accidents as traffic volume, pedestrian volume, number of Entry/exit, number of crosswalk and bus stop were adopted in the above model. CONCLUSIONS : The optimal model for pedestrian accidents is evaluated to be Tobit model.

• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.991-1002
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• 2014

Both Bayesian and maximum likelihood methods are efficient for the estimation of regression coefficients of various Tobit regression models (see. e.g. Chib, 1992; Greene, 1990; Lee and Choi, 2013); however, some researchers recognized that the maximum likelihood method tends to underestimate the disturbance variance, which has implications for the estimation of marginal effects and the asymptotic standard error of estimates. The underestimation of the maximum likelihood estimate in a seemingly unrelated Tobit regression model is examined. A Bayesian method based on an objective noninformative prior is shown to provide proper estimates of the disturbance variance as well as other regression parameters

• The Korean Journal of Applied Statistics
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• v.35 no.3
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• pp.357-370
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• 2022

In this paper, Tobit and Heckit models are introduced. These models have been used for analyzing censored data. Censoring occurs at a specific point and a large number of observations are distributed with a positive probability at a certain point. Censoring can occur due to observing limitation or exogenous variables. Tobit and Heckit models are used to correct sample selection bias, which can occur when an ordinary linear regression model is fitted to censored data. However, the difference between the two models is not clearly accounted for; hence, they have often been used interchangeably. Therefore, the suitability of the models was validated through simulated data, and demonstrated through real data. As the result, it was confirmed that both Tobit and Heckit models are well-fitted to the data censored due to observing limitation, although Tobit model was fitted parsimoniously. In contrast, only Heckit model is well-fitted to the data censored due to exogenous variables.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.12
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• pp.8719-8727
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• 2015

The purpose of this study is to examine the production efficiency of Rose farm and to explain the factors of the inefficiency. To analysis the production efficiency, SFA(Stochastic Frontier Analysis) and DEA(Data Envelopment Analysis) methods are measured, and then, Tobit regression model is used to analysis the influential factors on the production efficiency. As a result, first, the production efficiency by SFA is 88.4%, and by DEA, results are 78.5% and 85.2% in the CRS and VRS model, respectively. In particular, the production efficiency of the measurement results of the two methods are complementary, it is described in the same order of efficiency of each management body. Second, the results of tobit model shows that 6 input-factors are significant, and seed/nursery and material costs, which have the largest regression coefficient value and positive effect on production efficiency, are the most influential factors. Therefore, the results of this study indicates Rose farm can enhance their management efficiency by increasing amount of the seed/nursery and material costs.

• Korean Management Science Review
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• v.31 no.4
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• pp.135-150
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• 2014

This paper analyzes the operational efficiency of 91 individual retail stores in Seoul by a two-step procedure. In the first step, a data envelopment analysis (DEA) model is used to identify the efficiency scores. Three inputs (store size, number of items, and number of employees) and two outputs (sales and number of customers) are used for the efficiency measurement. In the second step, a Tobit regression model is used to identify the drivers of efficiency. DEA efficiency scores are used to test hypotheses on the impact of five independent variables, namely store age, number of items per store size, number of items per employee, trade area index, and number of competitors. Results of the Tobit analysis show that number of items per store size, number of items per employee, and number of competitors play a significant role in influencing the operational efficiency of retail stores. Managerial implications of the study are discussed.

• Journal of Preventive Medicine and Public Health
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• v.40 no.2
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• pp.145-149
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• 2007

Objectives : This study characterized the extent to which youth depressive symptoms, parental alcohol problems, and parental drinking account for differences in alcohol-related problems among a large sample of adolescent females. Methods : The stratified sample consists of 2077 adolescent females from twelve female-only high schools located in a large metropolitan city in the Republic of Korea. Students completed a questionnaire about alcohol use and alcohol problems, their parents' alcohol problems, and a number of risk and protective factors. Data were analyzed using tobit regression analyses to better characterize the associations among variables. Results : Almost two-thirds of students who consume alcohol had experienced at least one to two alcohol-related problems in their lives and 54.6% reported at least one current symptom of depression, with nearly one-third reporting two depressive symptoms. Two-thirds of the students indicated that at least one parent had an alcohol-related problem, and that approximately 29% had experienced several problems. Results of tobit regression analyses indicate that youth alcohol-related problems are positively associated with depressive symptoms (p<0.01) and parent drinking problems (p<0.05). Parental drinking is no longer significant when the variable parental attention is added to the model. Decomposition of the tobit parameters shows that for every unit of increase in depressive symptoms and in parent drinking problems, the probability of a youth experiencing alcohol problems increases by 6% and 1%, respectively. For every unit of increase in parental attention, the probability of youth experiencing drinking problems decreases by 5%. Conclusions : This study presents evidence that alcohol-related problems and depressive symptoms are highly prevalent among adolescent females. Although a comprehensive public health approach is needed to address drinking and mental health problems, different interventions are needed to target factors associated with initiation of alcohol problems and those associated with increased alcohol problems among those who already began experiencing such problems.

• Journal of Digital Convergence
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• v.19 no.10
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• pp.339-348
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• 2021

This paper aims to analyze the production efficiency in Korea's ten service sectors using DEA and its determinants utilizing a truncated-Tobit regression model and a censored-Tobit regression model in 2010-2019. This paper found: First, the Korean service sector's production efficiency in general has been significantly low and polarized. Especially, the inefficiency resulted from the scale inefficiency in the 'sewerage waste management industry.' Second, in the determinants analysis, the results show the positive effect of the investment and R&D expenses on technical efficiency, while FDI and lobbying expenses illustrate the negative impact. Moreover, it seems that the larger the industry, the higher the efficiency. Thus, the future Korean government's economic policy for the service sectors requires a mixed and integrated policy of the macroeconomic aspect such as active investment and R&D activities with microeconomic aspect including a convergence of FDI and human capital.

• Health Policy and Management
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• v.27 no.4
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• pp.296-303
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• 2017

Background: This study purposed to analyze regional factors related to gastric cancer screening rate provided by national cancer screening program in Korea. Methods: The unit of analysis was administrative districts of si gun gu level. Dependent variable was regional gastric cancer screening rate provided by national cancer screening program, and regional variables were selected to represent the regional characteristics such as demographic, health behavior and status, socioeconomic, and health resource. Tobit regression was applied for the analysis. Results: Analysis results showed that gastric cancer screening rate was varied depending on regions from 47.8% to 69.1%. Tobit regression showed that gastric cancer screening rate had negative relationships with smoking rate, financial independence rate, and National Health Insurance premium per capita. And regional gastric cancer screening rate had positive relationships with sex ratio and number of gastric cancer screening center. Conclusion: Regional characteristics should be considered in establishing regional policies for increasing the gastric cancer screening rate.