• 제목/요약/키워드: statistical design

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두 가지 복합 이상원인 영향이 있는 공정에 대한 VSS$\bar{x}$관리도의 경제적 설계 (The Economic Design of VSS $\bar{x}$ Control Chart for Compounding Effect of Double Assignable Causes)

  • 심성보;강창욱;강해운
    • 산업경영시스템학회지
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    • 제27권2호
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    • pp.114-122
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    • 2004
  • In statistical process control applications, variable sample size (VSS) $\bar{X}$ chart is often used to detect the assignable cause quickly. However, it is usually assumed that only one assignable cause results in the out-of-control in the process. In this paper, we propose the algorithm to minimize the function of cost per unit time and compare the economic design and the statistical design by use of the value of cost per unit time. We consider double assignable causes to occur with compound in the process and adopt the Markov chain approach to investigate the statistical properties of VSS $\bar{X}$ chart. A procedure that can calculate the control chart's parameters is proposed by the economic design.

Assessment of Bioequivalence with Dropout Subjects in 3$\times$3 and 3$\times$2 Crossover Design

  • Ko, seoung-gon;Oh, Hyun-Sook
    • Journal of the Korean Statistical Society
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    • 제29권2호
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    • pp.219-229
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    • 2000
  • Oh et al.(1999) 3$\times$2 crossover design for assessing bioequivalence when two new generic drug formulations and innovator are simultaneously considered. This design is not only more efficient than 3$\times$3 one, proposed by Lee et al.(1998), in practical sense, but also more ethical in medical sense. However, the general statistical methods are not directly applicable to both designs when subjects are dropped out in the experiment, even though it is always possible in bioavailability and bioequivalence studies because of some administrative and economic reasons. In this research we propose an inference to drug effects when subjects are dropped out in the planed-for 3$\times$3 and 3$\times$2 crossover experiments. An example is given for illustration.

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Nonparametric Tests for 2×2 Cross-Over Design

  • Gee, Kyuhoon;Kim, Dongjae
    • Communications for Statistical Applications and Methods
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    • 제19권6호
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    • pp.781-791
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    • 2012
  • A $2{\times}2$ Cross-over design is widely used in clinical trials for comparison studies of two kinds of drugs or medical treatments. This design has many statistical methods such as Hills-Armitage's (1979) method or Koch's (1972) method. In this paper, we propose a nonparametric test for $2{\times}2$ Cross-over design based on a two-sample test suggested by Baumgartner et al. (1998). In addition, a Monte Carlo simulation study is adapted to compare the power of the proposed methods with those of previous methods.

화학공학 분야에서 통계적 실험계획법 적용에 대한 서지 검토 (Application of Statistical Design of Experiments in the Field of Chemical Engineering: A Bibliographical Review)

  • 유계상
    • 공업화학
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    • 제31권2호
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    • pp.138-146
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    • 2020
  • 통계학적 실험계획법(DOE)은 수십 년 동안 산업계에서 품질을 개선하기 위해 사용되어온 방법이다. 본 연구에서는 화학공학 분야에서 통계적 실험계획법이 적용된 사례 115건을 검토해 보았다. 모든 사례는 지난 10년간 주요 과학저널에 발표된 내용이다. 적용되는 설계 유형, 실험 규모, 반응 변수에 영향을 미치는 요인 및 수준의 수 및 적용 분야가 분석되었다. 무엇보다 통계학적 실험계획법에 관련된 연구논문이 점차 증가하는 것을 알 수 있었다.

부품.소재산업 동향 조사의 표본설계 (Sample Design for Materials and Components Industry Trend Survey)

  • 남궁평
    • Communications for Statistical Applications and Methods
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    • 제15권6호
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    • pp.883-897
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    • 2008
  • 2006년 통계청이 시행한 광업 제조업 통계조사 결과(2005년 실적치)를 모집단으로 사용하면 최근 동향을 반영한 표본설계가 가능하다. 본 논문은 기존의 12개 업종보다 세분화된 94개 세부업종에 분류에 따라 매월 부품 소재산업의 생산, 출하, 재고의 변동사항을 조사하여 부품 소재산업의 경기변동실태를 파악하고 부품 소재산업의 육성정책 및 기업경영의 기초자료를 제공할 수 있는 새로운 표본설계를 제안한다. 표본설계는 응용절사법과 주성분을 이용한 다변량 네이만 배정법을 이용하여 층별로 표본크기를 결정하여 배정하고 표본추출은 확률비례계통추출을 사용한다.

강건 최적설계에서 통계적 모멘트와 확률 제한조건에 대한 효율적인 민감도 해석 (The Efficient Sensitivity Analysis on Statistical Moments and Probability Constraints in Robust Optimal Design)

  • 허재성;곽병만
    • 대한기계학회논문집A
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    • 제32권1호
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    • pp.29-34
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    • 2008
  • The efforts of reflecting the system's uncertainties in design step have been made and robust optimization or reliability-based design optimization are examples of the most famous methodologies. In their formulation, the mean and standard deviation of a performance function and constraints expressed by probability conditions are involved. Therefore, it is essential to effectively and accurately calculate them and, in addition, the sensitivity results are required to obtain when the nonlinear programming is utilized during optimization process. We aim to obtain the new and efficient sensitivity formulation, which is based on integral form, on statistical moments such as the mean and standard deviation, and probability constraints. It does not require the additional functional calculation when statistical moments and failure or satisfaction probabilities are already obtained at a design point. Moreover, some numerical examples have been calculated and compared with the exact solution or the results of Monte Carlo Simulation method. The results seem to be very satisfactory.

의학 논문 작성 시 발생하는 흔한 통계적 오류 (Statistical Mistakes Commonly Made When Writing Medical Articles)

  • 전소영;양주연;이혜선
    • 대한영상의학회지
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    • 제84권4호
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    • pp.866-878
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    • 2023
  • 의학 논문을 작성할 때 통계학은 필수적인 요소로 알려져 있고 중요성이 강조되고 있지만 많은 논문에서 통계적 오류가 발생하고 있다. 의학 논문에서 발생할 수 있는 통계적 오류는 설계 단계에서의 오류, 분석 단계에서의 오류, 작성과 해석 단계에서의 오류로 분류할 수 있다. 설계 단계에서는 연구의 가설이나 자료의 수집 및 분석 계획이 명확하지 않으면 오류가 발생한다. 분석 단계에서는 연구의 목적과 자료의 특성을 충분히 고려하지 않고 올바른 분석 방법을 적용하지 않으면 오류가 발생한다. 분석을 수행한 후에는 결과를 해석하여 논문을 작성하게 되고, 이 단계에서 분석 방법을 잘못 작성하거나 결과를 올바르게 해석하지 못하면 오류가 발생한다. 본 논문에서는 의학 논문에서 흔히 발생하는 통계적 오류에 대해 고찰하고 오류를 줄이는데 기여하고자 한다.

최적의 IC 설계와 통계적 분석을 위한 새로운 설계 환경 (A Novel Framework for Optimal IC Design and Statistical Analysis)

  • 이재훈;김경호;김영길;김경화
    • 전자공학회논문지A
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    • 제31A권3호
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    • pp.77-86
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    • 1994
  • A New environment SENSATION for circuit optimization and statistical analysis has been developed. It provides real time simulation and includes automatic algorithms to assist for reaching optimal solution. Furthermore, statistical analysis environment is presented which aids in Monte Carlo analysis. worst case corner analysis, and sensitivity analysis. These capabilities faciliate the characterization of the effects of several operating conditions and manufacture process paramenters on the design performances. We verify that the proposed methods can obtain the optimal solution of the objective function through several experimental results.

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$p^{n-m}$ fractional Factorial Design Excluded SOme Debarred Combinations

  • Choi, Byoung-Chul;Kim, Hyuk-Joo
    • Communications for Statistical Applications and Methods
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    • 제7권3호
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    • pp.759-766
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    • 2000
  • In order to design fractional factorial experiments which include some debarred combinations, we should select defining contrasts so that those combinations are to be excluded. Choi(1999) presented a method of selectign defining contrasts to construct orthogonal 3-level fractional factorial experiments which exclude some debarred combinations. In this paper, we extend Choi's method to general p-level fractional factorial experiments to select defining contrasts which cold exclude some debarred combinations.

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