Influence Diagnostics on Testing Linear Hypothesis in Linear Models with Correlated Errors

To assess the influence of observations on the parameter estimates, case deletion diagnostics are commonly used in linear regression models. For linear models with correlated errors we study the influence of observations on testing a linear hypothesis using single and multiple case deletions. The change in likelihood ratio test and F test theoretically is derived and it is shown these tests to be completely determined by two proposed generalized externally studentized residuals. An illustrative example of a real data set is also reported.     

Confidence intervals for the mean of a normal distribution with restricted parameter space

For a normal distribution with known variance, the standard confidence interval of the location parameter is derived from the classical Neyman procedure. When the parameter space is known to be restricted, the standard confidence interval is arguably unsatisfactory. Recent articles have addressed this problem and proposed confidence intervals for the mean of a normal distribution where the parameter space is not less than zero. In this article, we propose a new confidence interval, rp interval, and derive the Bayesian credible interval and likelihood ratio interval for general restricted parameter space. We compare these intervals with the standard interval and the minimax interval. Simulation studies are undertaken to assess the performances of these confidence intervals.     

Work performance and tax compliance in flat and progressive tax systems

Different tax systems, and their impact on work motivation and tax compliance are significant issues in contemporary political and economic debates. The proportional feature of a flat tax system is assumed to lead to higher performance, while the fairness of the redistributive progressive tax system is assumed to result in higher tax compliance. However, empirical findings on the topic are inconclusive. Both work performance and tax compliance under different tax systems were examined in an experiment, with special attention devoted to the effect of a change in tax systems. A flat tax system was supposed to induce greater work performance, whereas a progressive tax system was expected to increase tax compliance based on fairness perceptions, allowing for the opposite effect due to higher complexity. Furthermore, it was assumed that performance and tax payments would be influenced by motives of self-interest. The design included 20 rounds with a real-effort task in each round, determining participants’ experimental income. Participants (N = 191) made decisions about their tax payments from round-to-round in four different experimental conditions: (1) a flat tax system, (2) a progressive tax system, (3) starting with a flat and changing to a progressive, and (4) starting with a progressive and changing to a flat tax system. Results indicate higher work performance in a progressive system. However, a change from a progressive tax system to a flat system led to increased tax compliance.     

On an asymptotic relative efficiency concept based on expected volumes of confidence regions

ABSTRACT

The paper deals with an asymptotic relative efficiency concept for confidence regions of multidimensional parameters that is based on the expected volumes of the confidence regions. Under standard conditions the asymptotic relative efficiencies of confidence regions are seen to be certain powers of the ratio of the limits of the expected volumes. These limits are explicitly derived for confidence regions associated with certain plugin estimators, likelihood ratio tests and Wald tests. Under regularity conditions, the asymptotic relative efficiency of each of these procedures with respect to each one of its competitors is equal to 1. The results are applied to multivariate normal distributions and multinomial distributions in a fairly general setting.     

Modified likelihood ratio tests in heteroskedastic multivariate regression models with measurement error

In this paper, we develop modified versions of the likelihood ratio test for multivariate heteroskedastic errors-in-variables regression models. The error terms are allowed to follow a multivariate distribution in the elliptical class of distributions, which has the normal distribution as a special case. We derive the Skovgaard-adjusted likelihood ratio statistics, which follow a chi-squared distribution with a high degree of accuracy. We conduct a simulation study and show that the proposed tests display superior finite sample behaviour as compared to the standard likelihood ratio test. We illustrate the usefulness of our results in applied settings using a data set from the WHO MONICA Project on cardiovascular disease.     

男女性别比失衡问题的思考

目前,我国男女性别比例严重失衡,由此带来性犯罪现象增加、婚姻挤压、拜金主义思想等各种社会问题,究其原因,除了传统的重男轻女观念的影响和妇女地位的不平等外,还有科技手段的滥用。应该树立先进的社会性别意识,禁止非法的胎儿性别鉴定,提高女性的社会地位,这样,才能切实解决出生人口性别比例失调问题。     

Comparing diagnostic tests: test of hypothesis for likelihood ratios

Likelihood ratios (LRs) are used to characterize the efficiency of diagnostic tests. In this paper, we use the classical weighted least squares (CWLS) test procedure, which was originally used for testing the homogeneity of relative risks, for comparing the LRs of two or more binary diagnostic tests. We compare the performance of this method with the relative diagnostic likelihood ratio (rDLR) method and the diagnostic likelihood ratio regression (DLRReg) approach in terms of size and power, and we observe that the performances of CWLS and rDLR are the same when used to compare two diagnostic tests, while DLRReg method has higher type I error rates and powers. We also examine the performances of the CWLS and DLRReg methods for comparing three diagnostic tests in various sample size and prevalence combinations. On the basis of Monte Carlo simulations, we conclude that all of the tests are generally conservative and have low power, especially in settings of small sample size and low prevalence.     

Generalizing the standardized hazard ratio to multivariate proportional hazards regression,with an application to clinical~genomic studies

The standardized hazard ratio for univariate proportional hazards regression is generalized as a scalar to multivariate proportional hazards regression. Estimators of the standardized log hazard ratio are developed, with corrections for bias and for regression to the mean in high-dimensional analyses. Tests of point and interval null hypotheses and confidence intervals are constructed. Cohort sampling study designs, commonly used in prospective–retrospective clinical genomic studies, are accommodated.     

马克思主义人学理论的动态历史考察

马克思主义人学思想是一个非常完整、科学的理论体系,其形成和发展主要经历了三个发展阶段:从博士论文到《1844年经济学哲学手稿》是其萌芽时期,提出了以劳动为基础的人学理论框架;从《神圣家族》到《共产党宣言》是其基本形成和发展时期,确立了人学理论的唯物主义立场;从《共产党宣言》到《资本论》是其成熟和完善时期,形成了以人的自由全面发展为最终归宿的完备人学理论体系。马克思主义人学在唯物史观的基础上实现了对以往人学理论的超越,为人和社会的发展开辟了广阔的前景。