Evaluation of an analysis approach used to account for extra-variation in clustered categorical responses

This article presents the results of a simulation study investigating the performance of an approach developed by Miller and Landis (1991) for the analysis of clustered categorical responses. Evaluation of this “two-step” approach, which utilizes the method of moments to estimate the extra-variation pardmeters and subsequently incorporates these parameters into estimating equations for modelling the marginal expectations, is carried out in an experimental setting involving a comparison between two groups of observations. We assume that data for both groups are collected from each cluster and responses are measured on a three-point ordinal scale. The performance of the estimators used in both “steps” of the analysisis investigated and comparisons are made to an alternative analysismethod that ignores the clustering. The results indicate that in the chosen setting the test for a difference between groups generally operatbs at the nominal α=0.05 for 10 or more clusters and hasincreasing power with both an increasing number of clusters and an inrreasing treatment effect. These results provide a striking contrasc to those obtained from an improper analysis that ignores clustering.     

Bayesian Approaches to Nonparametric Estimation of Densities on the Unit Interval

This paper investigates nonparametric estimation of density on [0, 1]. The kernel estimator of density on [0, 1] has been found to be sensitive to both bandwidth and kernel. This paper proposes a unified Bayesian framework for choosing both the bandwidth and kernel function. In a simulation study, the Bayesian bandwidth estimator performed better than others, and kernel estimators were sensitive to the choice of the kernel and the shapes of the population densities on [0, 1]. The simulation and empirical results demonstrate that the methods proposed in this paper can improve the way the probability densities on [0, 1] are presently estimated.     

ON SOME OPTIMALITY PROPERTIES OF FISHER-RAO SCORE FUNCTION IN TESTING AND ESTIMATION

The score function is associated with some optimality features in statistical inference. This review article looks on the central role of the score in testing and estimation. The maximization of the power in testing and the quest for efficiency in estimation lead to score as a guiding principle. In hypothesis testing, the locally most powerful test statistic is the score test or a transformation of it. In estimation, the optimal estimating function is the score. The same link can be made in the case of nuisance parameters: the optimal test function should have maximum correlation with the score of the parameter of primary interest. We complement this result by showing that the same criterion should be satisfied in the estimation problem as well.     

项目教学法在PLC课程教学中的应用

PLC课程是职业院校电气工程类、机电一体化类及自动化类专业的主干专业课程之一。传统的教学方式很难提高学生的实践动手能力。引入项目教学法不但能够提高学生的实践动手能力,还能够让学生真正品尝到成功的喜悦,体验到成就感,认识到自己的智力潜能,提高学习的主动性和积极性,更能满足企业的用人需求。     

文化创意产业的规划与政策制定研究

文化创意产业宜以行政和市场“两个对接”作为基本分析方法，其产业的规划要求理清服务业的分类，实行文化制造业、文化服务业和文化贸易业并行发展。     

高校党校建设和创新的思路与举措

党的十七大报告明确提出，要以改革创新精神加强党的自身建设，为新时期、新阶段全面推进党的建设提供了指导原则和行动纲领。高校党校教育在高校党的建设和党的事业中具有重要的地位和作用。从3个方面阐述高校党校建设和创新的思路与举措：认清形势，坚定信念，加强高校党校建设工作；把握方向，深入研究，探索高校党校建设路径；解放思想，锐意改革，创新高校党校建设思路。     

A multivariate solution of the multivariate ranking and selection problem

The problem of selection of the best multivariate population is given a new formulation which does not involve reducing the populations to univariate quantities. This formulation's solution is developed for known, and (using the Heteroscedastic Method) also for unknown, variance-covariance matrices. Preference reversals and arbitrary nonlinear preference functions are explicitly allowed in this new theory     

高校服装工程专业课程考核方法的创新思考

围绕现行课程考核方法的价值和存在的主要问题等方面的分析,总结指出高校服装工程专业加快课程考核改革创新体制的建设,不仅是构建高校服装工程专业实践性、创新型人才的实施途径和保障,全面提升服装工程专业学生创新素质的根本需要,而且对于推动高校服装工程专业发展都有着深远的现实意义。     

分析电磁散射问题的MGFFT方法

采用多重网格法（ＭＧ）分析电大尺寸物体的电磁散射，这种ＭＧ方法与已有的几种多重矩量法有本质的不同，与其他多层方法相比，它是一种高效率的迭代方法。再利用积分方程的卷积特性引入ＦＦＴ方法快速计算迭代过程中矩阵与矢量的乘积，从而构成ＭＧＦＦＴ新算法，数值结果表明ＭＧＦＦＴ方法具有很高的计算效率，适用于电大尺寸问题的分析。     

An asymptotic confidence interval for the process capability index Cpm

Abstract

The use of indices as an estimation tool of process capability is long-established among the statistical quality professionals. Numerous capability indices have been proposed in last few years. C_pm constitutes one of the most widely used capability indices and its estimation has attracted much interest. In this paper, we propose a new method for constructing an approximate confidence interval for the index C_pm. The proposed method is based on the asymptotic distribution of the index C_pm obtained by the Delta Method. Under some regularity conditions, the distribution of an estimator of the process capability index C_pm is asymptotically normal.