• Proceedings of the Korean Association for Survey Research Conference
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• 2001.06a
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• pp.45-56
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• 2001

In this paper, we conducted an empirical study to investigate the design and weighting effects on descriptive and analytic statistics. We compared the regression models using the design-based approach and the generalized estimating equations(GEEs) approach with the model-based approach through the design and weighting effects analysis.

• Journal of the Korean Data and Information Science Society
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• v.20 no.6
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• pp.1155-1167
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• 2009

We made a new sample design for life and consciousness survey of Kyungpook people in 2007. We used the 10% sample survey data of 2005 population and housing census as a survey population. After stratification, we allocate proportionally samples within strata after examining various characteristics in previous survey, which includes economic activity state, an income level per year, and housing possession. And we calculated weight in a new sample design and derived estimators and a formula of standard error using the weights.

• The Korean Journal of Applied Statistics
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• v.21 no.4
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• pp.675-694
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• 2008

We propose a new sampling design for the Korean Livestock Production Cost Survey. In this sampling design, the survey population is derived from the 2005’s agricultural census of Korea. And coefficient of variation(CV) is estimated from the current livestock production cost survey data, and the estimated CV’s are used to find the optimal sample size which satisfies the predetermined precision of estimation. In order to save the enumeration cost, the agriculture enumeration districts are used as a primary sampling unit(psu). Final sample is selected by double sampling. Also, we propose the estimator which is able to reflect the change of the population of livestock production households.

• Journal of the Korean Data and Information Science Society
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• v.21 no.4
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• pp.669-679
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• 2010

A sample survey design is suggested for the service satisfaction evaluation of regional education offices based on the sample size of 2009 Gyeongnam regional education offices's customer satisfaction survey. The sample design is developed to fit the goal of evaluation of individual regional offices and allocate at least the minimum sample size to each city or county in Gyeongnam to achieve the goal of the survey. The population is stratified according to the regions and the types of schools, and the sample of schools is selected with proportional to the size of classes within each stratum. Finally, each sample student is selected according to two-stage cluster sampling within each sample school. Weighting averages, weighting totals and so on can be evaluated for analysis purposes. Their variance estimates can be evaluated using re-sampling methods like BBR, Jackknife, linearization-substitution methods, which are generally used for the data from a complex sample.

• Journal of the Korea Convergence Society
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• v.11 no.10
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• pp.387-392
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• 2020

This study was to investigate the relationship of BMI, sleep time and experience of oral diseases in adolescents. We want to help develop basic data for improving oral health of adolescents. According to the sample design of the Youth Health Behavior online survey, a total of 57,303 adolescents were analyzed for frequency of composite samples, x2-test of composite samples, and logistic regression of composite samples, and the IBM SPSS Statistics 20.0 program was used and the significance level was 0.05. Results, BMI was associated with bad breath, and sleep time was associated with tooth break, pain, bleeding, and bad breath. Therefore, BMI and sleep time should be considered for the management and prevention of oral diseases in adolescents.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.21-28
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• 2017

This study aims to identify individual and familial factors associated with youth sexual experience by using the nationally representative sample data in South Korea. Specifically, we select 68,043 students in middle and high schools participating in the 2015 Korea Youth Risk Behavior Web-based Survey. Considering the complex survey design, we conduct a descriptive analysis and multiple logistic regression for sexual experience. The main results identify factors on sexual experience such as age, type of school, stress level, drinking, smoking, economic status, and cohabiting parents. In particular, the drinking and smoking behaviors are positively associated with sexual experience and the youth living with neither parent is more likely to have a sexual experience than those who lived two parents. In conclusion, the plan of sex education should consider the risk factors and the quality of sex education should be enhanced in order to build more appropriate sexual culture and behaviors among the youth.

• The Korean Journal of Applied Statistics
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• v.24 no.6
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• pp.1115-1128
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• 2011

Cut-off sampling that discards a part of the population from the sampling frame, is a widely used method for a highly skewed population like a business survey. Usually to the estimate of population total, we need to estimate the total of the take-nothing stratum. Many estimators have been developed to estimate the total of the take-nothing stratum. In this paper, we suggest a new composite estimator which combines the estimator suggested by Sarndal et al. (1992) and a ratio estimator obtained by small samples from the take-nothing stratum. Small simulation studies are performed for the comparison of the estimators and we confirm that the new suggested estimator is superior to the others.

• The Korean Journal of Applied Statistics
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• v.31 no.5
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• pp.587-597
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• 2018

Procedures, such as sampling technique, survey method, and questionnaire preparation, are required in order to obtain sample data in accordance with the purpose of a survey. An important procedure is the decision of the sample size formula. The sample size formula is determined by setting the target error and total cost according to the sampling method. In this paper, we propose a sample size formula using population changes over time, estimation error of the previous time and response rate of past data when the target error and the expected response rate are given in the simple random sampling. In actual research, we use estimators that apply complex weights in addition to design-based weights. Therefore, we induce a sample size formula for estimators using design-based weights and nonresponse adjustment coefficients, that can be a formula that reflects differences in response rates when survey methods are changed over time. In addition, we use simulations to compare the proposed formula with the existing sample size formula.

• Communications for Statistical Applications and Methods
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• v.17 no.4
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• pp.515-525
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• 2010

We investigated design-based properties of the ordinary least square estimator(OLSE) and the weighted least square estimator(WLSE) in a panel regression model. Given a complex data we derive the magnitude of the design-based bias of two estimators and show that the bias of WLSE is smaller than that of OLSE. We also conducted a simulation study using Korean welfare panel data in order to compare design-based properties of two estimators numerically. In the study we found the followings. First, the relative bias of OLSE is nearly two times larger than that of WLSE and the bias ratio of OLSE is greater than that of WLSE. Also the relative bias of OLSE remains steady but that of WLSE becomes smaller as the sample size increases. Next, both the variance and mean square error(MSE) of two estimators decrease when the sample size increases. Also there is a tendency that the proportion of squared bias in MSE of OLSE increases as the sample size increase, but that of WLSE decreases. Finally, the variance of OLSE is smaller than that of WLSE in almost all cases and the MSE of OLSE is smaller in many cases. However, the number of cases of larger MSE of OLSE increases when the sample size increases.

• Journal of Digital Convergence
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• v.19 no.4
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• pp.167-176
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• 2021

This study aims to analyze economically active females' factors influencing problematic drinking, by their jobs. It examined the socio-demographic and health-related characteristics and problematic drinking status of economically active females over 19, by using data from the 6th Korea National Health and Nutrition Examination Survey. They were analyzed by using IBM SPSS 25.0 and the complex sampling design. The findings show that the problematic drinking rates of economically active females were varied by their jobs: 19.1% for office job; 24.8% for manufacturing job; 12.3% for service job. The factors influencing problematic drinking were also differed by jobs: subjective heath status for office job; marital status and smoking for service job; marital status for manufacturing job. They suggest that convergent drinking management programs customized to jobs should be developed by considering the characteristics of females' physical and emotional traits and their jobs, to reduce their problematic drinking rates.