• Communications for Statistical Applications and Methods
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• v.4 no.2
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• pp.333-343
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• 1997

선형회귀분석에서 변수의 선택문제는 최적의 모형을 찾는데 아주 중요한 부분을 차지한다. George와 McCulloch(1993)는 계층적 베이즈 모형과 깁스표본법을 이용하여 선형회귀모형에서 변수를 선택하는 문제를 고려하였다. 이 논문에서는 George와 McCulloch의 모형을 바탕으로 각각의 설명변수가 모형에 포함될 사전확률을 객관적인 기준에 의하여 결정하는 문제를 고려하여 보았다.

• Communications for Statistical Applications and Methods
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• v.5 no.3
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• pp.819-826
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• 1998

임의중도 절단된 이 표본의 수명자료에서 누적위험함수의 비는 시간의 변화에 따른 두 집단의 위험률을 서로 비교할 수 있는 수단이 된다. 본 논문에서는 먼저 두 집단의 누적위험함수의 비에 대한 추정량을 제안하고, 제안된 추정량의 점근성을 유도하였다. 또한 누적위험함수의 비에 대한 여러 가지 동시신뢰대들을 제안하였으며, 실제 자료에 적용하여 보았다.

• Proceedings of the Korean Association for Survey Research Conference
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• 2000.06a
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• pp.105-112
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• 2000

대부분 통계조사에서 흔히 발생하는 무응답을 처리하기 위한 방법으로 최근에는 표본 대체 방법이 널리 이용되고 있다. 본 논문에서는 여러 가지 표본 대체 방법을 소개하고 각 방법의 장. 단점을 비교. 설명한다. 그리고 대체된 데이터를 응답 데이터인 것처럼 활용했을 때 발생하는 문제점들을 지적하고 모의 실험을 통하여 그 정도를 살펴본다. 이와 더불어 제기된 문제점을 해결하는 몇 가지 해결방안을 소개한다.

• Communications for Statistical Applications and Methods
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• v.3 no.1
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• pp.111-120
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• 1996

1992년 국민인체측정조사 결과를 이용하여 도시규모, 거주권역에 따른 체위차이유무를 검증한다. 분석결과에 따르면 남자의 경우 청소년층에서 거주권역별 체위차이가 나타났으며, 반면 여자의 경우 장년층에서 그 차이를 나타났다. 본 연구는 이러한 분석결과를 이용하여 보다 경제적인 조사를 수행하기 위한 개선된 표본설계를 제안한다.

• The Korean Journal of Applied Statistics
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• v.26 no.5
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• pp.747-758
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• 2013

The covariance matrix is important in multivariate statistical analysis and a sample covariance matrix is used as an estimator of the covariance matrix. High dimensional data has a larger dimension than the sample size; therefore, the sample covariance matrix may not be suitable since it is known to perform poorly and event not invertible. A number of covariance matrix estimators have been recently proposed with three different approaches of shrinkage, thresholding, and modified Cholesky decomposition. We compare the performance of these newly proposed estimators in various situations.

• The Korean Journal of Applied Statistics
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• v.18 no.3
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• pp.597-606
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• 2005

The nonresponse in sample survey causes a problem when it comes time to analyze dataset in public-use files where the user has only complete-data methods available and has limited information about the reasons for nonresponse. Recently imputation for nonresponse is becoming a standard approach for handling nonresponse and various imputation methods have been devised . However, most imputation methods concern with continuous traits while many interesting features are measured by binary or ordered categorical scales in sample survey. In this note. an imputation method for ignorable nonresponse in binary or ordered categorical traits is considered.

• The Korean Journal of Applied Statistics
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• v.8 no.2
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• pp.109-119
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• 1995

A two sample chi-square test is introduced for testing the equality of the distributions of two populations when observations are subject to random censorship. The statistic is appropriate in testing problems where a two-sided alternative is of interest. Under the null hypothesis, the asymptotic distribution of the statistic is a chi-square distribution. We obtain two types of chi-square statistics ; one as a nonnegative definite quadratic form in difference of observed cell probabilities based on the product-limit estimators, the other one as a summation form. Data pertaining to a cancer chemotheray experiment are examined with these statistics.

• Communications for Statistical Applications and Methods
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• v.5 no.3
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• pp.675-684
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• 1998

지가변동율조사는 전국의 지가변동상황을 조사하여 국가 토지정책 수행을 위한 기초자료로 활용되고 있다. 새로운 표본설계는 지가변동율조사의 부차모집단인 전국 246개 시·군·구 내에서 각 토지의 용도지역 구분과 실제이용상황을 고려하여 층화하였다 또한 각 시 군· 구에서 평균지가지수의 상대표준오차를 일정하게 관리하였고, 각 용도지역별 최소표본수를 배정하여 발표되는 용도지역별 지가지수와 변동율의 신뢰성을 높였다.

• The Korean Journal of Applied Statistics
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• v.26 no.4
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• pp.595-610
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• 2013

Testing of order-restricted alternative hypothesis in $2{\times}k$ contingency tables can be applied to various fields of medicine, sociology, and business administration. Most testing methods have been developed based on a large sample theory. In the case of a small sample size or unbalanced sample size, the Type I error rate of the testing method (based on a large sample theory) is very different from the target point of 5%. In this paper, the exact testing method is introduced in regards to the testing of an order-restricted alternative hypothesis in categorical data (particularly if a small sample size or extreme unbalanced data). Power and exact p-value are calculated, respectively.

• The Korean Journal of Applied Statistics
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• v.11 no.2
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• pp.269-285
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• 1998

One of the most important issues in the area of clinical trial research is the determination of the sample size required to insure a specified power in detecting a real or clinically relevant difference of a stated magnitude. Increasingly, medical journals are requiring authors to provide information on the sample size needed to detect a given difference. We restrict our attention to the designs far comparirng two survival distributions. These are concerned with the survival time which is defined as the interval from a baseline(e.g. randomization) to failure (e.g. death, recurrence of disease). Survival times axe right censored when patients have not foiled by the time of analysis or have been loss to follow-up during the trial. For different types of clinical trials for comparing survival distributions, there have been marry research in sample size determination. We review the existing literature concerning commonly used sample size formulae in the design of randomized clinical trials, and compare the assumption, the power and the sample size calculation of these methods. We also compare by simulation the expected power and observed power of each method under various circumstances. As a result, guidelines in terms of practical usage are provided.