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收集所有交通大學研究人員與學生個人或團體所發表之各項學術著作，涵蓋期刊論文、教師專書、學位論文等項。;;Collections of Publications of NCTU Researchers and Students Like Journal Papers and Thesis.

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Author: search.filters.author.Shieh, GwowenSubject: search.filters.subject.power

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Now showing 1 - 6 of 6
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    Power Analysis and Sample Size Planning in ANCOVA Designs
    (2020-03-01)
    Shieh, Gwowen
    ;
    交大名義發表
    ;
    管理科學系
    ;
    National Chiao Tung University
    ;
    Department of Management Science
    The analysis of covariance (ANCOVA) has notably proven to be an effective tool in a broad range of scientific applications. Despite the well-documented literature about its principal uses and statistical properties, the corresponding power analysis for the general linear hypothesis tests of treatment differences remains a less discussed issue. The frequently recommended procedure is a direct application of the ANOVA formula in combination with a reduced degrees of freedom and a correlation-adjusted variance. This article aims to explicate the conceptual problems and practical limitations of the common method. An exact approach is proposed for power and sample size calculations in ANCOVA with random assignment and multinormal covariates. Both theoretical examination and numerical simulation are presented to justify the advantages of the suggested technique over the current formula. The improved solution is illustrated with an example regarding the comparative effectiveness of interventions. In order to facilitate the application of the described power and sample size calculations, accompanying computer programs are also presented.
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    Determining Sample Size With a Given Range of Mean Effects in One-Way Heteroscedastic Analysis of Variance
    (2013-07-03)
    Shieh, Gwowen
    ;
    Jan, Show-Li
    ;
    交大名義發表
    ;
    管理科學系
    ;
    National Chiao Tung University
    The authors examined 2 approaches for determining the required sample size of Welch's test for detecting equality of means when the greatest difference between any 2 group means is given. It is shown that the actual power obtained with the sample size of the suggested approach is consistently at least as great as the nominal power. However, the sample size given by the method of Guo and Luh (2008) does not always guarantee the minimum power performance. Furthermore, the computed sample size and associated power of their formula tend to be larger than those provided with the proposed procedure. A supplementary computer program is provided to aid the implementation of the proposed technique in planning analysis of variance designs.
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    Optimal Sample Size Determinations for the Heteroscedastic Two One-Sided Tests of Mean Equivalence: Design Schemes and Software Implementations
    (2017-04-01)
    Jan, Show-Li
    ;
    Shieh, Gwowen
    ;
    管理科學系
    ;
    Department of Management Science
    Equivalence assessment is becoming an increasingly important topic in many application areas including behavioral and social sciences research. Although there exist more powerful tests, the two one-sided tests (TOST) procedure is a technically transparent and widely accepted method for establishing statistical equivalence. Alternatively, a direct extension of Welch's solution for the Behrens-Fisher problem is preferred in equivalence testing of means when the homogeneity of variance assumption is violated. For advance planning of equivalence studies, this article describes both exact and nearly exact power functions of the heteroscedastic TOST procedure and develops useful approaches to optimal sample size determinations under various allocation and cost considerations. Detailed numerical illustrations and simulation studies are presented to demonstrate the distinct features of the suggested techniques and the potential deficiency of existing method. Moreover, computer programs are provided to facilitate the implementation of the described sample size procedures. The proposed formulas and algorithms are recommended over the current results for their technical transparency, overall performance, and diverse utility.
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    Sample Size Determination for Examining Interaction Effects in Factorial Designs Under Variance Heterogeneity
    (2018-03-01)
    Shieh, Gwowen
    ;
    交大名義發表
    ;
    管理科學系
    ;
    National Chiao Tung University
    ;
    Department of Management Science
    Moderation analysis is a vital aspect of research in education, management, psychology, and related disciplines. Although several methodological artifacts have been identified and examined, heterogeneity of variance remains one of the unique and problematic factors known as detrimental to statistical power in the detection of moderating effects. To alleviate the difficulty in assessing moderation because of low statistical power, this article describes feasible solutions to sample size calculations for tests of hypothesized interactions between categorical variables under variance heterogeneity. Detailed numerical illustrations and simulation studies are presented to demonstrate the feature and usefulness of the suggested technique for 2- and 3-way factorial designs. Moreover, SAS and R programs are provided to facilitate the implementation of the proposed sample size procedure.
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    Power and Sample Size Calculations for Contrast Analysis in ANCOVA
    (2017)
    Shieh, Gwowen
    ;
    管理科學系
    ;
    Department of Management Science
    Analysis of covariance (ANCOVA) is commonly used in behavioral and educational research to reduce the error variance and improve the power of analysis of variance by adjusting the covariate effects. For planning and evaluating randomized ANCOVA designs, a simple sample-size formula has been proposed to account for the variance deflation factor in the comparison of two treatment groups. The objective of this article is to highlight an overlooked and potential problem of the exiting approximation and to provide an alternative and exact solution of power and sample size assessments for testing treatment contrasts. Numerical investigations are conducted to reveal the relative performance of the two procedures as a reliable technique to accommodate the covariate features that make ANCOVA design particularly distinctive. The described approach has important advantages over the current method in general applicability, methodological justification, and overall accuracy. To enhance the practical usefulness, computer algorithms are presented to implement the recommended power calculations and sample-size determinations.
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    Detecting Interaction Effects in Moderated Multiple Regression With Continuous Variables Power and Sample Size Considerations
    (2009-07-01)
    Shieh, Gwowen
    ;
    交大名義發表
    ;
    National Chiao Tung University
    In view of the long-recognized difficulties in detecting interactions among continuous variables in moderated multiple regression analysis, this article aims to address the problem by providing feasible solutions to power calculation and sample size determination for significance test of moderating effects. The proposed approach incorporates the essential factors of strength of moderator effect, magnitude of error variation, and distributional property of predictor and moderator variables into a unified framework. Accordingly, careful consideration across different plausible and practical configurations of the prescribed factors is an important aspect of power and sample size computations in planning moderated multiple regression research. The performance of the suggested procedure and an alternative simplified method is illustrated with detailed numerical studies. The simulation results demonstrate that an acceptable degree of accuracy can be obtained using the recommended method in assessing moderated relationships.