• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.477-483
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• 2015

This study deals with the decision problem of sample size by the relative standard error of estimates derived from survey results in successive occasions. The population of the construction in business survey results is used to calculate quartile of the relative standard error of the 1,000 sample obtained from simple or stratified random sampling. The sample size at time t with a relative standard error of the point (t-1) in the successive occasions were calculated according to the sampling method. As a result, in terms of the sample size according to the size of the relative standard error of the (t-1), simple random sampling differs significantly from stratified sampling. In addition, we could see differences in sample size (depending on how the population is stratified) and that careful attention is required in the problem of sample size by the relative standard error of estimates derived from survey results in successive occasions.

• The Korean Journal of Applied Statistics
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• v.14 no.2
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• pp.289-304
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• 2001

2001년에 실시할 $\ulcorner$국민건강.영양조사$\lrcorner$를 위한 새로운 표본설계를 하였다. 본 표본설계에서는 표본의 대표성을 높이기 위해서 기존의 표본가구수는 유지하면서 표본조사구를 증가시키고 새로운 지역 층화변수를 추가로 도입하였다. 또한 추정량의 추정오차 공식을 유도하여 추정의 신뢰성을 측정할 수 있도록 설계하였다.

• Proceedings of the Korean Statistical Society Conference
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• 2005.11a
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• pp.91-96
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• 2005

다차원층화에서 선형계획법을 이용한 표본배정 방법은 Winkler(1990, 2001), Sitter와 Skinner(1994, 2002)가 제안하였다. 이 방법들은 표본크기가 층 개수보다 크지 않는 경우에 공통적으로 선형계획법을 이용하여 표본배정을 실시하였다. 반복 비율 적합방법(IPF), 일반화 반복 비율 적합(GIFP), SS 방법을 통해 셀 값을 결정하고 선형계획법을 이용하여 표본의 배정확률을 통해 표본배정을 실시한다. 이 3가지 방법들로 표본을 배정하고 평균 및 분산추정량을 비교한다.

• Communications for Statistical Applications and Methods
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• v.1 no.1
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• pp.157-164
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• 1994

본 연구에서는 확률화응답기법을 이용하여 모집단내의 민감집단의 비율을 추정함에 있어 조사의 효율성을 높이기 위한 층화표본의 최적할당방법을 제안한다. 확률화응답기법은 Warner(1965)에 의하여 제안된 방법으로 민감한 사안에 대한 조사시 무응답이나 거짓응답으로 인한 비표본오차를 줄일수 있는 기법으로 간접질문에 의한 조사방법이다. 여기에서 최적할당이란 베이즈위험을 최소로 하는 할당법을 의미하며, 이 과정에서 민감집단의 모비율에 대한 사전분포로는 베타분포를 취하였다.

• The Korean Journal of Applied Statistics
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• v.36 no.4
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• pp.337-347
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• 2023

Sampling designs often use stratified sampling, where elements or clusters of the study population are divided into strata and an independent sample is chosen from each stratum. The stratification strategy consists of stratification and sample allocation, which are important issues that are repeatedly considered in survey sampling. Although a stratified multistage sample design is often used in practice, the literature tends to discuss simple sampling in terms of stratum effects or stratum efficiency. This study examines an existing stratum efficiency measure for two-stage sampling and further proposes additional stratum efficiency measures using the design effect model. The proposed measures are used to evaluate the stratification strategy of the sample design for high school students of the 4^th Korean National Environmental Health Survey (KoNEHS).

• The Korean Journal of Applied Statistics
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• v.26 no.2
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• pp.209-222
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• 2013

We apply stratified cluster sampling to a replicated systematic unrelated question model for a large scale survey in which the population is comprised of several strata developed by several clusters and with sensitive parameters. We first present a replicated systematic unrelated question model using an unrelated question model to procure sensitive information from the population of clusters and then develop a suggested model to an unrelated question by a stratified cluster replicated systematic sampling that can be used in large population of strata. We cover the proportional and optimum allocation for the suggested model. Finally, we compare and analyze the efficiency of the suggested model with the replicated systematic unrelated question model.

• The Korean Journal of Applied Statistics
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• v.12 no.1
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• pp.175-190
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• 1999

생존시간을 비교하기 위한 임상시험에서는 생존기간과 관련된 위험인자들을 고려한 층화된 연구설계가 종종 요구된다. 이 경우 필요한 표본수가 결정은 층이 없는 경우에 비하여 다양한 연구상황과 복잡한 표본수의 산출 절차를 수반한다. 본 논문에서는 층이 있는 경우 생존시간을 비교할 때 필요한 표본수를 결정하는 방법들을 실례와 함께 설명하고, 연구자가 주어진 상황하에서 적절한 방법을 선택하는데 도움이 될 수 있도록, 다양한 상황을 설정하여 이에 대한 표본수를 비교하였다.

• The Korean Journal of Applied Statistics
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• v.8 no.1
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• pp.27-38
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• 1995

In the surveys of sensitive issues of the population that is composed of several unknown-size stratum, we propose the unrelated question model with quantitative attribute by using stratified double sampling. And, we consider two types of sample allocations under the fixed cost, which are the proportional allocation, the optimum allocation. In efficiency, the proosed model is inferior to the unrelated question model with quantitative attribute by stratified sampling in case of the size of each stratum is known. But we find that efficiency of the proposed model is increased, when the selecting probability of sensitive question p is small and first stage sample size n' is large.

• Survey Research
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• v.11 no.3
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• pp.103-114
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• 2010

It is difficult to obtain the population information of target variables when a new sampling design for successive survey is executed. In a research of the Korea National Tourism Survey, we propose a method for selection of efficient stratification variables which are found in a combination of a existing sample data and a new frame list. At first, if there isn't common identification number between the frame list and the sample data, we find a device to substitute for absence of identification number. At second, we suggest a method to search stratification variables correlated with target variables using statistical methods like regression analysis.

• The Korean Journal of Applied Statistics
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• v.11 no.2
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• pp.233-246
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• 1998

We made a sample design for next 5 years, based on the population as of 1995, for livestock statistics. In the sample design, we used the stratified one stage sampling method where the sample size depends on the prefixed coefficient of variation. In stratifying the population, we considered the complete linkage method, and decided the number of strata to be the one which yields the minimum sample size. We listed here some difficulties we had for the better sample design in the future.