Leader-member exchange and organizational citizenship behaviors: Contextual effects of leader power distance and group task interdependence

In this paper we explore the context of the relationship between leader-member exchange and organizational citizenship behaviors (OCB). We maintain that workgroup leader's power distance and the extent of task interdependence in the group exert cross-level effects on the LMX-OCB relationship. We assert that leader power distance attenuates the relationship between LMX and OCB, and this effect is stronger in workgroups with high degree of task interdependence. Results of hierarchical linear modeling analysis of data gathered from 245 employees nested in 54 workgroups supported our hypotheses. LMX-OCB relationship was weaker in workgroups led by high power distance leaders. Further, the three-way cross-level interaction between LMX, leader power distance and group task interdependence demonstrated that the tendency for LMX to have a stronger positive effect on OCB when leader power distance was low rather than high was more pronounced in high task interdependence teams.     

基于混合加权距离的毕达哥拉斯模糊TOPSIS多属性决策方法研究

针对决策信息为毕达哥拉斯模糊集的多属性决策问题，提出了一种基于混合加权测度的TOPSIS决策方法。在分析了现有距离测度方法不足的基础上，首先给出了一种新的毕达哥拉斯模糊距离测度——毕达哥拉斯模糊有序加权距离（PFOWD），并研究了该测度权重的确定方法；在PFOWD基础上，进一步提出了毕达哥拉斯模糊混合加权距离（PFHWD），同时探讨了其特征和与现有毕达哥拉斯模糊测度的关系；最后提出了一种基于PFHWD测度的毕达哥拉斯模糊TOPSIS多属性方法，并用实例验证了方法的有效性和可行性。     

校园网与现代教育

探讨了校园网和现代教育的关系 ,校园网络可以成为现代教育的平台和核心 ,围绕着校园网建设面向未来的现代教育 ,着重阐述了校园网络建设应该注意的问题。     

ASSESSING CONGRUENCEAMONG DISTANCE MATRICES: SINGLE-MALT SCOTCH WHISKIES REVISITED

A test of congruence among distance matrices is described. It tests the hypothesis that several matrices, containing different types of variables about the same objects, are congruent with one another, so they can be used jointly in statistical analysis. Raw data tables are turned into similarity or distance matrices prior to testing; they can then be compared to data that naturally come in the form of distance matrices. The proposed test can be seen as a generalization of the Mantel test of matrix correspondence to any number of distance matrices. This paper shows that the new test has the correct rate of Type I error and good power. Power increases as the number of objects and the number of congruent data matrices increase; power is higher when the total number of matrices in the study is smaller. To illustrate the method, the proposed test is used to test the hypothesis that matrices representing different types of organoleptic variables (colour, nose, body, palate and finish) in single‐malt Scotch whiskies are congruent.     

Markov chain Monte Carlo methods for high dimensional inversion in remote sensing

Summary.  We discuss the inversion of the gas profiles (ozone, NO₃, NO₂, aerosols and neutral density) in the upper atmosphere from the spectral occultation measurements. The data are produced by the 'Global ozone monitoring of occultation of stars' instrument on board the Envisat satellite that was launched in March 2002. The instrument measures the attenuation of light spectra at various horizontal paths from about 100 km down to 10–20 km. The new feature is that these data allow the inversion of the gas concentration height profiles. A short introduction is given to the present operational data management procedure with examples of the first real data inversion. Several solution options for a more comprehensive statistical inversion are presented. A direct inversion leads to a non-linear model with hundreds of parameters to be estimated. The problem is solved with an adaptive single-step Markov chain Monte Carlo algorithm. Another approach is to divide the problem into several non-linear smaller dimensional problems, to run parallel adaptive Markov chain Monte Carlo chains for them and to solve the gas profiles in repetitive linear steps. The effect of grid size is discussed, and we present how the prior regularization takes the grid size into account in a way that effectively leads to a grid-independent inversion.     

Goodness of fit for the inverse Gaussian distribution

For testing the fit of the inverse Gaussian distribution with unknown parameters, the empirical distribution-function statistic A² is studied. Two procedures are followed in constructing the test statistic; they yield the same asymptotic distribution. In the first procedure the parameters in the distribution function are directly estimated, and in the second the distribution function is estimated by its Rao-Blackwell distribution estimator. A table is given for the asymptotic critical points of A². These are shown to depend only on the ratio of the unknown parameters. An analysis is provided of the effect of estimating the ratio to enter the table for A². This analysis enables the proposal of the complete operating procedure, which is sustained by a Monte Carlo study.     

Assessing accuracy of a continuous screening test in the presence of verification bias

Summary.  In studies to assess the accuracy of a screening test, often definitive disease assessment is too invasive or expensive to be ascertained on all the study subjects. Although it may be more ethical or cost effective to ascertain the true disease status with a higher rate in study subjects where the screening test or additional information is suggestive of disease, estimates of accuracy can be biased in a study with such a design. This bias is known as verification bias. Verification bias correction methods that accommodate screening tests with binary or ordinal responses have been developed; however, no verification bias correction methods exist for tests with continuous results. We propose and compare imputation and reweighting bias-corrected estimators of true and false positive rates, receiver operating characteristic curves and area under the receiver operating characteristic curve for continuous tests. Distribution theory and simulation studies are used to compare the proposed estimators with respect to bias, relative efficiency and robustness to model misspecification. The bias correction estimators proposed are applied to data from a study of screening tests for neonatal hearing loss.     

Influence diagnostics and outlier tests for semiparametric mixed models

Summary. Semiparametric mixed models are useful in biometric and econometric applications, especially for longitudinal data. Maximum penalized likelihood estimators (MPLEs) have been shown to work well by Zhang and co-workers for both linear coefficients and nonparametric functions. This paper considers the role of influence diagnostics in the MPLE by extending the case deletion and subject deletion analysis of linear models to accommodate the inclusion of a nonparametric component. We focus on influence measures for the fixed effects and provide formulae that are analogous to those for simpler models and readily computable with the MPLE algorithm. We also establish an equivalence between the case or subject deletion model and a mean shift outlier model from which we derive tests for outliers. The influence diagnostics proposed are illustrated through a longitudinal hormone study on progesterone and a simulated example.     

对网络教学的分析和探讨

随着知识经济的发展 ,网络已经日渐走入人们的生活并且开始显示其重要性。同时 ,社会对教育模式、教育手段都提出了新的要求。网络教学作为一种新型的教育方式 ,在我国迅速发展起来 ,并且成为远程教育的重要形式之一。本文就网络教学的学习理论、特点、定位以及现阶段我国网络教学与发达国家网络教学的差距进行了分析和探讨 ,并对我国网络教学今后的发展方向和需要解决的问题 ,提出了个人的见解。