• Communications for Statistical Applications and Methods
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• 제8권3호
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• pp.667-675
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• 2001

The usefulness of analysis of variance(ANOVA) estimates of variance components is impaired by the frequent occurrence of negative values. The probability of such an occurrence is therefore of interest. In this paper, we investigate a variety of reasons for negative estimates under one way random effects model. It can be shown, through simulation, that this probability increases when the number of treatments is too small for fixed total observations, unbalancedness of data is severe, ratio of variance components is too small, and data may contain many outliers.

• 한국임상수의학회지
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• 제27권1호
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• pp.71-78
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• 2010

Analysis of variance (ANOVA) is a method to analyze the data from the experimental designs comparing two or more groups or treatments at the same time, and is the most effective tool of analyzing more complex data sets with different source of variations. This article describes the logic of ANOVA, the application of the method to the analysis of a simple data set, and the methods available for performing planned or post hoc multiple comparisons between the treatments means. In addition, the common misuse of the techniques is also discussed to emphasize that an inappropriate statistical analysis is potentially far more harmful than poorly conducted research. Lastly, an example is given for illustration purposes.

• Journal of the Korean Statistical Society
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• 제35권3호
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• pp.317-329
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• 2006

In the problem of estimating the error variance in the balanced fixed- effects one-way analysis of variance (ANOVA) model, Ghosh (1994) proposed hierarchical Bayes estimators and raised a conjecture for which all of his hierarchical Bayes estimators are admissible. In this paper we prove this conjecture is true by representing one-way ANOVA model to the distributional form of a multiparameter exponential family.

• Journal of the Korean Data and Information Science Society
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• 제13권2호
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• pp.317-328
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• 2002

We first derive group ordering reference priors in a two-way mixed-effects analysis of variance (ANOVA) model. We show that posterior distributions are proper and provide marginal posterior distributions under reference priors. We also examine whether the reference priors satisfy the probability matching criterion. Finally, the reference prior satisfying the probability matching criterion is shown to be good in the sense of frequentist coverage probability of the posterior quantile.

• Communications for Statistical Applications and Methods
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• 제9권2호
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• pp.315-324
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• 2002

For estimating the error variance under the relative squared error loss in two-way analysis of variance models, we provide a class of hierarchical Bayes estimators and then derive a subclass of the hierarchical Bayes estimators, each member of which dominates the best multiple of the error sum of squares which is known to be minimax. We also identify a subclass of non-minimax hierarchical Bayes estimators.

• International Journal of Computer Science & Network Security
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• 제24권4호
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• pp.44-50
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• 2024

This paper offers an overview of matrix formation and calculation techniques within the framework of General Linear Models (GLMs). It takes a sequential approach, beginning with a detailed exploration of matrix formation and calculation methods in regression analysis and univariate analysis of variance (ANOVA). Subsequently, it extends the discussion to cover multivariate analysis of variance (MANOVA). The primary objective of this study was to provide a clear and accessible explanation of the underlying matrices that play a crucial role in GLMs. Through linking, essentially different statistical methods, by fundamental principles and algebraic foundations that underpin the GLM estimation. Insights presented here aim to assist researchers, statisticians, and data analysts in enhancing their understanding of GLMs and their practical implementation in diverse research domains. This paper contributes to a better comprehension of the matrix-based techniques that can be extended to GLMs.

• 응용통계연구
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• 제15권2호
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• pp.405-414
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• 2002

반복이 같은 이원배치 혼합효과 분산분석모형에서 무정보 사전분포를 이용하여 오차분산을 추정하는 문제를 생각하고자 한다. 먼저 무정보 사전분포로 제프리스사전분포, 준거 사전분포 그리고 확률일치 사전분포를 유도하고 이들 각각의 사전분포들에 대하여 주변사후분포를 제시하였다. 끝으로 실제 자료를 근거로 오차분산의 주변사후밀도함수에 대한 그래프와 오차분산에 대한 신용구간들을 구하고 이 구간들을 비교한다.

• 응용통계연구
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• 제17권3호
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• pp.419-430
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• 2004

마이크로어레이 기술은 한번에 수만 개의 유전자를 동시에 분석할 수 있는 고효율, 고가의 새로운 연구 도구로 자리잡았으며 마이크로어레이 실험 자료의 올바른 분석을 위해서는 실험 목적에 맞는 실험계획법의 확립과 통계분석법의 적용이 중요하다 본 논문에서는 마이크로어레이 자료에서 여러 군 사이에서 발현의 차이를 보이는 유전자를 찾을 수 있는 되돌림 설계를 소개하고 ANOVA 모형을 이용하여 분석하는 방법을 제시한다. 연세대학교 암전이 연구센터의 되돌림 설계를 이용한 백혈병 자료를 MA-ANOVA(Wu et. al.(2003))를 이용하여 분석하였다

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2001년도 춘계학술대회 논문집
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• pp.1008-1011
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• 2001

The purpose of this paper is to evaluate the chip breakability during turning using the experimental equation, which is developed by an orthogonal array method. The chip breaking index(CB), non-dimensional parameter is used in the evaluation of chip breakability. The analysis of variance(ANOVA)-test has been used to check the significance of cutting parameters. And using the result of ANOVA-test, the experimental equation of chip breakability, which consists of significant cutting parameters, has been developed.

• 한국국방경영분석학회지
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• 제13권1호
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• pp.45-64
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• 1987

Power algorithms for analysis of variance tests are presented. In experimental design of operational tests and evaluations the selection of design parameters so as to attain an experiment with desired power is a difficult and important problem. An interactive computer program is presented which uses the power algorithms for ANOVA tests and creates graphical presentations which can be used to assist decision makers in statistical design. ANOVA tests and associated parameters (such as sample size, types and levels of treatments, and alpha-level)are examined.