• Proceedings of the Korean Association for Survey Research Conference
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• 2007.06a
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• pp.139-149
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• 2007

사회조사를 위한 표본설계를 할 때 표본의 크기를 얼마로 할 것인지를 결정하는 문제는 조사연구자에게 고민거리가 된다. 사회조사 중에서 4점 또는 5점 척도로 된 여러 개의 개별 문항들로 구성된 설문지를 사용하는 경우가 많다. 이런 경우 개개의 문항 자체를 직접적으로 하나의 변수로 사용하지 않고 여러 개 문항들을 결합하여 새로운 척도를 만들어 사용하는 것이 일반적이다. 본 연구의 목적은 리커트 척도가 관심변수인 조사연구에서 표본크기를 결정하는 방법을 제공하는 것이다. 리커트 척도를 만들고자 할 때 4점 혹은 5점 척도로 구성된 여러 문항변수들은 일반적으로 서로 양의 상관관계를 가지게 된다. 본 연구에서는 개별 문항변수들은 각각 동일한 분포를 가지며, 각각의 변수들은 서로 동일한 크기의 상관관계를 갖는다는 가정을 한다. 주어진 가정 하에서 새로운 척도의 표본분포를 유도한 후 이를 이용하여 다양한 상황에서의 표본의 크기를 계산한 결과를 표로 제시하게 되는데 표본이론을 잘 모르는 조사연구자들은 이 표를 이용하여 원하는 표본크기를 결정 할 수 있을 것이다.

• The Korean Journal of Applied Statistics
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• v.11 no.2
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• pp.403-413
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• 1998

Sample size determination is a crucial part of sampling design. This paper gives a assessment for sample size determination using two-stage sampling scheme for estimating the population mean with a given precision.

• The Korean Journal of Applied Statistics
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• v.12 no.2
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• pp.593-603
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• 1999

표본의 크기의 제1종오류의 확률 $\alpha$, 실용적으로 차이가 있다고 판독되어서 검출하고자하는 요인효과의 오차에 대한 상대적인 크기, 그 값에서의 제2종오류의 확률 $\beta$에 따라서 결정된다. 이 논문에서, 우리는 고정요인과 랜덤요인이 포함된 실험계획에서 표본의 크기를 결정하는 방법을 간단한 MATLAB 프로그램을 사용하여 고려한다. 분할법과 지분요인배치법의 예제를 들어 유의수준 $\alpha$와 최소 표준과 검출효과 $\Delta^*$에서 검정력이 적어도 $1-\beta$를 갖도록 표본의 크기를 결정한다

• Communications for Statistical Applications and Methods
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• v.4 no.2
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• pp.403-409
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• 1997

일단-집락 추출을 할 때에 예비표본으로 부터 얻은 정보를 활용하여 추가표본을 추출한다. 특히, 예비표본의 크기(예비표본의 집락의수) $n_1$ 과 추가표본의 크기$n_2$를 모두 변수로 간주하여 베이즈 위험을 최소로 하는 $n_1$과 $n_2$의 크기를 결정한다.

• Journal of the Korean Data and Information Science Society
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• v.23 no.1
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• pp.53-61
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• 2012

There are cases when the sample size is determined based not only on the significance level but also on on the power or type II error. In this paper, we implemented the sample size and the power calculation when both the significance level and power for testing means in normal distributions and proportions in binomial distributions. The implementation is available on a web site. Alternately, we also calculate the power for a given effect size, type I error probability and sample size.

• The Korean Journal of Applied Statistics
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• v.28 no.3
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• pp.573-581
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• 2015

We study problems of sample size determination for one-sample location tests. A simulation study shows that sample size calculations based on approximated distribution do not achieve the nominal level of power. We investigate sample size determinations based on exact distribution and with a power that attains the nominal level.

• The Korean Journal of Applied Statistics
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• v.27 no.4
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• pp.513-521
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• 2014

If the target error of an estimator at the present time is greater than the coefficient of variation(CV) of the estimator at the previous time, sample size at this point should be decreased. Various papers have researched sample size determination methods using the CV of an estimator at the previous time, variation of population size and target error of the estimator at this time in sampling on successive occasions. We research a new sample size determination method additionally using change of population CV. We compare the proposed method with existing ones in various simulation settings.

• 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 Data and Information Science Society
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• v.27 no.5
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• pp.1317-1325
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• 2016

The purpose of this paper is to explain the factors affecting the wage of the vocational high school graduates. We particularly examine the effectiveness of controlling sample selection bias by employing the Tobit model and Heckman sample selection model. The major results are as follows. First it is shown that the Tobit model and Heckman sample selection model controlling sample selection bias is statistically significant. Hence all the independent variables seem to be statistically consistent with the theoretical model. Second, gender was statistically significant, both in the probability of employment and the wage. Third, the employment probability and wage of Maester high school graduates were shown to be high compared to all other graduates. Fourth, the higher parent's income, the higher are both the employment probability and the wage. Finally, parents education level, high school grade, satisfaction, and a number of licenses were found to be statistically significant, both in the probability of employment and wages.

• The Korean Journal of Applied Statistics
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• v.13 no.2
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• pp.207-224
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• 2000

Generally cluster size is predetermined when we use the stratified two-stage cluster sampling But in case that the sizes of clusters vary greatly one may want to make the sizes to be about equal. In this paper we study the optimal cluster size in stratified twostage cluster sampling. Also we find the optimal primary sampling unit sizes and optimal secondary sampling unit sizes under the given cost restriction.