• Communications for Statistical Applications and Methods
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• v.19 no.1
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• pp.13-22
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• 2012

Cut-off sampling that discards a part of the population from the sampling frame, is a widely used method for a business survey. Usually, to the estimate of population total, an accurate estimate of the total of the take-nothing stratum is required. Many estimators have been developed to estimate the total of the take-nothing stratum. Recently Kim and Shin (2011) suggested a composite estimator and showed the superiority of that estimator. In this paper, we suggest an alternative composite estimator obtained by combining BLUP estimator and a ratio estimator obtained by the small samples from the take-nothing stratum. Small simulation studies are performed for a comparison of the estimators and we confirm that the new suggested estimator is superior.

• Journal of the Korea Society of Computer and Information
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• v.27 no.6
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• pp.139-147
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• 2022

This study tried to analyze the relationship among physical activity level, subjective health status, COVID-19 Fear. This study used the 2020 Community Health Survey that includes 229,269 survey data from adults over 19 years old. The complex sampling design was applied including weight, stratification, cluster variables. Through the SPSS statistics program with complex sampling frequency analysis, complex sampling Chi-square and complex sampling regression, this study found followings. First, the group with high level of physical activity showed higher level of subjective health status than the group with low level of physical activity. Second, the group with high level of physical activity showed lower level of COVID-19 fear than the group with low level of physical activity. Third, the group with high level of subjective health status showed lower level of COVID-19 fear than the group with low level of subjective health status. However, this study has the limitation that this study did not check whether participant is diagnosed with Covid-19 or not.

• The Korean Journal of Applied Statistics
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• v.25 no.3
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• pp.447-456
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• 2012

For a sensitive survey in which the population is comprised of several clusters with a quantitative attribute, we present an additive quantitative randomized response model by cluster sampling that adapts a two-stage cluster sampling instead of a simple random sample based on Himmelfarb-Edgell's additive quantitative attribute model and Gjestvang-Singh's one. We also derive optimum values for the number of 1st stage clusters and the optimum values of observation units in a 2nd stage cluster under the condition of minimizing the variance given constant cost. We can see that Himmelfarb-Edgell's model is more efficient than Gjestvang-Singh's model under the condition of cluster sampling.

• Journal of Forest and Environmental Science
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• v.31 no.2
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• pp.73-77
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• 2015

Acquiring accurate quantitative and qualitative information is necessary for the technical and scientific management of forest stands. In this study, stratification and systematic random sampling methods were used to estimation of quantitative characteristics in study area. The estimator ($((E%)^2xT)$) was used to compare the systematic random and stratified sampling methods. 100 percent inventory was carried out in an area of 400 hectares; characteristics as: tree density, crown cover (canopy), and basal area were measured. Tree density of stands was compared through systemic random and stratified sampling methods. Findings of the study reveal that stratified sampling method gives a better representation of estimates than systematic random sampling.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.20
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• pp.8563-8569
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• 2014

Sub-optimal participation is a major problem with cervical cancer screening in developing countries which have no organized national screening program. There are various notable factors such as 'embarrassment', 'discomfort' and 'no time' cited by women as they are often also the bread winners for the family. Implementation of self-sampling methods may increase their participation. The aim of this article was to provide a survey of various types of self-sampling tools which are commonly used in collection of cervical cells. We reviewed currently available self-sampling devices and collated the advantages and disadvantages of each in terms of its acceptance and its accuracy in giving desired results. In general, regardless of which device is used, self-sampling for cervical scrapings is highly acceptable to women in most of the studies cited.

• Communications for Statistical Applications and Methods
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• v.25 no.1
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• pp.1-13
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• 2018

In many studies, a researcher attempts to describe a population where units are measured for multiple outcomes, or responses. In this paper, we present an efficient procedure based on ranked set sampling to estimate and perform hypothesis testing on a multivariate mean. The method is based on ranking on an auxiliary covariate, which is assumed to be correlated with the multivariate response, in order to improve the efficiency of the estimation. We showed that the proposed estimators developed under this sampling scheme are unbiased, have smaller variance in the multivariate sense, and are asymptotically Gaussian. We also demonstrated that the efficiency of multivariate regression estimator can be improved by using Ranked set sampling. A bootstrap routine is developed in the statistical software R to perform inference when the sample size is small. We use a simulation study to investigate the performance of the method under known conditions and apply the method to the biomarker data collected in China Health and Nutrition Survey (CHNS 2009) data.

• Survey Research
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• v.12 no.1
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• pp.153-174
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• 2011

This research aims to discuss the causes of inaccuracy in public opinion polls currently conducted in Korea. In particular, identifying the problems in sampling frame and sampling methods in political and social public opinion polls is an important question. Currently, most polling organizations operating in Korea are using phone number directories provided by Korea Telecom(KT) as its sampling frame for conducting most political polls. A critical problem of using a phone number directory as a sampling frame is that unlisted phone numbers can never be included in the sample. If a systematic difference in socio-demographic or politico-economic characteristics exists between the listed number using group and the unlisted group, using a phone number directory as a sampling frame cannot produce a sample that can represent the whole adult population in Korea. According to the poll result commissioned by the Asan Institute for Policy Studies in January 2011, there are statistically significant differences in socio-demographic and politico-economic characteristics between those two groups, and those differences led to the differences in the presidential job approval rating and party support. Our findings include that the listed number using group is more pro-Grand National Party and show stronger support for the president than the unlisted group.

• The Korean Journal of Applied Statistics
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• v.27 no.1
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• pp.43-59
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• 2014

Cut-off sampling has been widely used for a highly skewed population like a business survey by discarding a part of the population, so called a take-nothing stratum. For a more accurate estimate of the population total, Hwang and Shin (2013) suggested a composite estimator of a take-nothing stratum total that combined the survey results of a take-nothing stratum and a take-some sub-stratum (a part of take-some stratum). In this paper we propose a new cut-off sampling scheme by considering a cost function and a composite estimator based on the proposed sampling scheme. Small simulation studies compared the performances of known composite estimators and the new composite estimator suggested in this study. We also use Briquette Consumption Survey data for real data analysis.

• Survey Research
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• v.8 no.2
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• pp.91-115
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• 2007

OES survey as the national official statistics aims to provide the basic data for the national labor market policy and research such as the basic statistics for human resource supply policy, the prediction of employment by occupations, the decision of occupation, the occupational training and the finding jobs et al., at the levels of industrial and occupational classifications(3-digit). In order to achieve this objective, we analyze the OES data in 2005 and 2006 and propose the new sampling design using the long form data in Korea (10% sample data of census 2005). In this paper, we provide the criterion of sample allocation and derive the formular for estimator and error of it including the weighting procedure. From the proposed sampling design, we would expect that it contributes to the supply policy of human resource and the research for labor market.

• The Korean Journal of Applied Statistics
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• v.35 no.4
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• pp.485-499
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• 2022

Controlling the total survey error including sampling error and non-sampling error is very important in sampling design. Non-sampling error caused by non-response accounts for a large proportion of the total survey error. Many studies have been conducted to handle non-response properly. Recently, a lot of non-response imputation methods using machine learning technique and traditional statistical methods have been studied and practically used. Most imputation methods assume MCAR(missing completely at random) or MAR(missing at random) and few studies have been conducted focusing on MNAR (missing not at random) or NN(non-ignorable non-response) which cause bias and reduce the accuracy of imputation. In this study, we propose a non-response imputation method that can be applied to non-ignorable non-response. That is, we propose an imputation method to improve the accuracy of estimation by removing the bias caused by NN. In addition, the superiority of the proposed method is confirmed through small simulation studies.