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共線性對檢測調節效用的影響
(2010)
謝國文
;
Shieh Gwowen
;
國立交通大學管理科學系（所）
調節複廻歸已廣泛應用於兩連續式變數交互作用分析，而兩變數和其交互相乘項間的共線性對檢測的影響，自然地成為重要議題。本文試圖探索變數間相關程度對檢測調節效用的可能正面幫助，藉以釐清普遍以為共線性對調節複廻歸分析百害而無一利的誤解。針對簡單雙變數及三變數交互作用模式的理論解析和數據驗證，所獲結果有助於改變學者對變數間高度相關現象的憎惡，更提昇調節效用研究方法的實用價值。
A comparison of two approaches for power and sample size calculations in logistic regression models
(2000)
Shieh, G
;
管理科學系
;
Department of Management Science
Whittemore (1981) proposed an approach for calculating the sample size needed to test hypotheses with specified significance and power against a given alternative for logistic regression with small response probability. Based on the distribution of covariate, which could be either discrete or continuous, this approach first provides a simple closed-form approximation to the asymptotic covariance matrix of the maximum likelihood estimates, and then uses it to calculate the sample size needed to test a hypothesis about the parameter. Self et al. (1992) described a general approach for power and sample size calculations within the framework of generalized linear models, which include logistic regression as a special case. Their approach is based on an approximation to the distribution of the likelihood ratio statistic. Unlike the Whittemore approach, their approach is not limited to situations of small response probability. However, it is restricted to models with a finite number of covariate configurations. This study compares these two approaches to see how accurate they would be for the calculations of power and sample size in logistic regression models with various response probabilities and covariate distributions. The results indicate that the Whittemore approach has a slight advantage in achieving the nominal power only for one case with small response probability. It is outperformed for all other cases with larger response probabilities. In general, the approach proposed in Self et al. (1992) is recommended for all values of the response probability. However, its extension for logistic regression models with an infinite number of covariate configurations involves an arbitrary decision for categorization and leads to a discrete approximation. As shown in this paper, the examined discrete approximations appear to be sufficiently accurate for practical purpose.
An ANOVA test for the equivalency of means under unequal variances
(2000-04-28)
Chen, SY
;
Chen, HJ
;
Ding, CG
;
經營管理研究所
;
Institute of Business and Management
In this paper, we present a two-stage test procedure for testing the hypothesis that the normal means are falling into a practically indifferent zone. Both the level and the power associated with the proposed test are controllable and are completely independent of the unknown variances. Relation to a single-stage procedure is discussed when the two-stage sampling procedure cannot be completely carried through. An example and tables needed for implementation are given. (C) 2000 Elsevier Science B.V. All rights reserved.
Sample size calculations for logistic and Poisson regression models
(2001-12-01)
Shieh, G
;
管理科學系
;
Department of Management Science
A method is proposed for improving sample size calculations for logistic and Poisson regression models by incorporating the limiting value of the maximum likelihood estimates of nuisance parameters under the composite null hypothesis. The method modifies existing approaches of Whittemore (1981) and Signorini (1991) and provides explicit formulae for determining the sample size needed to test hypotheses about a single parameter at a specified significance level and power. Simulation studies assess its accuracy for various model configurations and covariate distributions. The results show that the proposed method is more accurate than the previous approaches over the range of conditions considered here.
Power analysis for linear models with spherical errors
(2002-11-01)
Wang, WJ
;
Wells, MT
;
統計學研究所
;
Institute of Statistics
In this article, we consider testing a general linear hypothesis for a regression model when the error distribution belongs to the class of spherical distributions. The distributional robustness of the F-statistics under a null hypothesis for spherically symmetric distributions is well understood. This invariance property, however, does not hold under the alternative hypothesis. Motivated by a simplified example, we study the relationship between power of the test and the error distribution's dispersion and kurtosis. We find that these two parameters are not sufficiently precise measures for determining the power behavior of a test. (C) 2002 Elsevier Science B.V. All rights reserved.
Distributional and inferential properties of the estimated precision C-p based on multiple samples
(2003-11-01)
Pearn, WL
;
Yang, YS
;
工業工程與管理學系
;
Department of Industrial Engineering and Management
Process precision index C-p has been widely used in the manufacturing industry to provide numerical measures on process potential. Pearn et al. ( 1998) considered an unbiased estimator of C-p for one single sample. They showed that the unbiased estimator is the UMVUE. They also proposed an efficient test for C-p based on one single sample, and showed that the test is the UMP test. In this paper, we consider an unbiased estimator of C-p for multiple samples. We show that the unbiased estimator is the UMVUE of C-p, which is asymptotically efficient. We also consider an efficient test for C-p, and show that the test is the UMP test for multiple samples. The practitioners can use the proposed test on their in-plant applications to obtain reliable decisions.
The effectiveness of randomized complete block design
(2004-02-01)
Shieh, G
;
Jan, SL
;
管理科學系
;
Department of Management Science
This paper examines the relative efficiency of randomized complete block design as compared with that of completely randomized design. The most widely used measure of relative efficiency considers only the error variances of the two designs, therefore it does not provide the complete information concerning the sensitivity of the experiment in the final results. We study three alternative criteria related to the sensitivity issue and design planning consideration. The proposed relative measures employ the p-value, Scheffe confidence interval estimation and power of both designs. The distinct feature of this study is the focus on the estimated relative efficiency measures and their relation with the coefficient of partial determination between responses and block effects, given that treatment effects are present in the models. Furthermore, informative visual representations and numerical assessments of various aspects of their properties are also presented.
Hot-carrier effects on power characteristics of SiGeHBTs
(2004-06-01)
Huang, SY
;
Chen, KM
;
Huang, GW
;
Tseng, HC
;
Hsu, TL
This letter investigates hot-carrier (HQ effects on the power characteristics of Si-SiGe HBTs using load-pull measurements. We found that the output power, power gain, and linearity of Si-SiGe HBTs are degraded after HC stress. Under constant base-current measurement, the HC-induced power performance degradation is found to be much worse than that under constant collector-current measurement. The HC effects on the cutoff frequency, nonlinearity terms of base-current and collector-current, and third-order intermodulation (IM3) cancellation effect have been analyzed to explain the experimental observations.
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.
Generalized inferences on the common mean of several normal populations
(2005-10-01)
Lin, SH
;
Lee, JC
;
統計學研究所
;
資訊管理與財務金融系註：原資管所+財金所
;
Institute of Statistics
The hypothesis testing and interval estimation are considered for the common mean of several normal populations when the variances are unknown and possibly unequal. A new generalized pivotal is proposed based on the best linear unbiased estimator of the common mean and the generalized inference. An exact confidence interval for the common mean is also derived. The generalized confidence interval is illustrated with two numerical examples. The merits of the proposed method are numerically compared with those of the existing methods with respect to their expected lengths, coverage probabilities and powers under different scenarios. (c) 2004 Published by Elsevier B.V.

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