• 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.

• Journal of the Korean Society of Safety
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• v.28 no.1
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• pp.158-163
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• 2013

While job stress evaluations are reported in the recent surveys upon the nuclear power plants(NPPs), any significant advance in the types of questionnaires is not currently found. There are limitations to their usefulness as analytic tools for the management of safety resources in NPPs. Data mining(DM) has emerged as one of the key features for data computing and analysis to conduct a survey analysis. There are still limitations to its capability such as dimensionality associated with many survey questions and quality of information. Even though some survey methods may have significant advantages, often these methods do not provide enough evidence of causal relationships and the statistical inferences among a large number of input factors and responses. In order to address these limitations on the data computing and analysis capabilities, we propose an advanced procedure of survey analysis incorporating the DM method into a statistical analysis. The DM method can reduce dimensionality of risk factors, but DM method may not discuss the robustness of solutions, either by considering data preprocesses for outliers and missing values, or by considering uncontrollable noise factors. We propose three steps to address these limitations. The first step shows data mining with response surface method(RSM), to deal with specific situations by creating a new method called response surface data mining(RSDM). The second step follows the RSDM with detailed statistical relationships between the risk factors and the response of interest, and shows the demonstration the proposed RSDM can effectively find significant physical, psycho-social, and environmental risk factors by reducing the dimensionality with the process providing detailed statistical inferences. The final step suggest a robust stress management system which effectively manage job stress of the workers in NPPs as a part of a safety resource management using the surrogate variable concept.

• Journal of Fisheries and Marine Sciences Education
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• v.26 no.5
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• pp.979-990
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• 2014

Recently the frequency of coastal disasters caused by global warming is increasing and the damage is becoming greater. Therefore, the Korean government is establishing various policies and measures to minimize damage. For disaster prevention, this study will evaluate the disaster response capacity of each local resident(Eup/Myeun/Dong) in coastal areas through the survey. The purpose of this study is to quantitatively understand the disaster response capacity and analyze spatial autocorrelation between hot spots(vulnerable area) and cold spots. Thus this study was conducted a survey of 311 towns(Eup/Myeun/Dong) about the disaster response capacity of coastal residents. As a result, Namhae has the highest average score(4.9). On the contrary, Hampyeong has the lowest(1.6). Coastal residents in Namhae seem to have better understanding of first aid and preventive maintenance. But coastal residents in Hampyeong seem to not have these characteristics. Afterwards, this study builds a database of disaster response capacity, and analyzes it using the spatial autocorrelation method. Finally, the area of hot spots and cold spots for disaster response capacity was quantitatively detected.

• Korean Journal of Childcare and Education
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• v.20 no.2
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• pp.169-194
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• 2024

Objective: The purpose of this study is to develop a child-care support policy strategy in response to the decrease in the population of children aged 0-5 years. This will be achieved by collecting opinions from a panel of experts on child-care support policies through a Delphi survey. Methods: To achieve the purpose of this study, a panel of 20 experts in child-care policy was selected, and a Delphi survey was conducted over three sessions. Data collected through the Delphi survey underwent analysis, including frequency analysis, descriptive statistics, content validity ratio, coefficient of variation, agreement, and convergence. Data processing was carried out using Excel 2016 and SPSS 26.0. Results: As a result of the study, a child-care support policy strategy addressing the decrease in the population of children aged 0-5 years was developed, comprising three policy areas, nine policy tasks, and 38 detailed policy tasks. Conclusion/Implications: Based on these results, it is anticipated that the study will not only enable the preparation of a strategy for child-care support policy to address the decrease in the population of children aged 0-5 years but also offer significant implications for shaping the direction of child-care support policy in alignment with the common good.

• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.761-770
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• 1999

A combination procedure of successive occasions sampling and randomized response method is investigated. Randomized response technique is very simple for use in a telephone survey of a sensitive subject. In the suggested randomized response method. the interviewee replies "yes" or "no" to a randomly selected question and the investigator can estimate the proportion of "yes" or "no" answer. When this procedure is used on successive occasions, not only the proportion supporting a candidate and the time change in this supporting proportion can be derived but also the voters' swing in the trend of voters' support can be estimated. A numerical example is given to show how the suggested sampling strategy can be applied to a practical telephone survey.

• Proceedings of the KIEE Conference
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• summer
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• pp.671-673
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• 2004

Demand Response Programs (DRP) are critical to the operation of efficient and competitive energy markets. and provide critical market improvements to Independent System Operators (ISO). To all energy market Participants, they Provide savings and cost reductions when end users have the ability to respond to wholesale prices. Now, in the competitive electricity market, DRP is classified by Emergency and Economic DRP to reduce costs and maintain reliability. In this paper, we survey the trend of Demand Response Program over the world and compare the practical performance among the markets in US.

• Communications for Statistical Applications and Methods
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• v.26 no.1
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• pp.11-25
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• 2019

The present paper utilizes auxiliary information to neutralize the effect of non-response for estimating the population mean. Improved ratio type estimators for population mean have been proposed and their properties are studied. These estimators are suggested for both single phase sampling and two phase sampling in presence of non-response. Empirical studies are conducted to validate the theoretical results and demonstrate the performance of the proposed estimators. The proposed estimators are shown to perform better than those used by Cochran (Sampling Techniques (3rd ed), John Wiley & Sons, 1977), Khare and Srivastava (In Proceedings-National Academy Science, India, Section A, 65, 195-203, 1995), Rao (Randomization Approach in Incomplete Data in Sample Surveys, Academic Press, 1983; Survey Methodology 12, 217-230, 1986), and Singh and Kumar (Australian & New Zealand Journal of Statistics, 50, 395-408, 2008; Statistical Papers, 51, 559-582, 2010) under the derived optimality condition. Suitable recommendations are put forward for survey practitioners.

• Journal of the Korean Statistical Society
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• v.32 no.2
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• pp.103-119
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• 2003

Properties of stochastic regression imputation are discussed under the uniform within-cell response model. Variance estimator is proposed and its asymptotic properties are discussed. A limited simulation is also presented.

• Journal of the Korean Data and Information Science Society
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• v.13 no.2
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• pp.341-354
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• 2002

This paper is planned to use randomized response technique which is an indirect response technique on internet as a way of obtaining much more precise information, not revealing secrets of responsors, considering that respondents are generally reluctant to answer in a survey to get sensitive information targeting employees, customers, etc.

• Journal of the Korean Data and Information Science Society
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• v.14 no.3
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• pp.591-603
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• 2003

This paper is planned to use randomized response technique which is an indirect response technique on internet as a way of obtaining much more precise information, not revealing secrets of responsors, considering that respondents are generally reluctant to answer in a survey to get sensitive information targeting employees, customers, etc.