Simulated classical tests in multinomial probit models

This paper compares the application of different versions of the simulated counterparts of the Wald test, the score test, and the likelihood ratio test in one- and multiperiod multinomial probit models. Monte Carlo experiments show that the use of the simple form of the simulated likelihood ratio test delivers relatively robust results regarding the testing of several multinomial probit model specifications. In contrast, the inclusion of the Hessian matrix of the simulated loglikelihood function into the simulated score test and (in the multiperiod multinomial probit model) particularly the inclusion of the quasi-maximum likelihood theory into the simulated likelihood ratio test leads to substantial computational problems. The combined application of the quasi-maximum likelihood theory with the simulated Wald test or the simulated score test is not systematically superior to the application of the other versions of these two simulated classical tests either. Neither an increase in the number of observations nor in the number of random draws in the incorporated Geweke-Hajivassiliou-Keane simulator systematically lead to more precise conformities between the frequencies of type I errors and the basic significance levels. An increase in the number of observations only decreases the frequencies of type II errors, particularly regarding the simulated classical testing of multiperiod multinomial probit model specifications.     

直接与间接——语言应用中的对立统一

直接与间接是矛盾的,同时又是统一的.这种对立统一主要体现在直接言语行为和间接言语行为、直接测试和间接测试以及直接教学法和间接教学法三方面.     

A survey on multivariate chi-square distributions and their applications in testing multiple hypotheses

We are concerned with three different types of multivariate chi-square distributions. Their members play important roles as limiting distributions of vectors of test statistics in several applications of multiple hypotheses testing. We explain these applications and consider the computation of multiplicity-adjusted p-values under the respective global hypothesis. By means of numerical examples, we demonstrate how much gain in level exhaustion or, equivalently, power can be achieved with corresponding multivariate multiple tests compared with approaches which are only based on univariate marginal distributions and do not take the dependence structure among the test statistics into account. As a further contribution of independent value, we provide an overview of essentially all analytic formulas for computing multivariate chi-square probabilities of the considered types which are available up to present. These formulas were scattered in the previous literature and are presented here in a unified manner.     

Small-Sample Improved Seasonal Unit Root Tests for Trending and Breaking Series

In this article three unit root tests that allow for a break in both the seasonal mean and linear trend of the data are proposed. The tests, which can be seen as small-sample corrected versions of already known asymptotic tests, are shown to perform very well in simulations, and much better than their asymptotic counterparts.     

Unit Root Tests in the Presence of Multi-Variance Break and Level Shifts That Have Power Against the Piecewise Stationary Alternative

Structural breaks in the level as well as in the volatility have often been exhibited in economic time series. In this paper, we propose new unit root tests when a time series has multiple shifts in its level and the corresponding volatility. The proposed tests are Lagrangian multiplier type tests based on the residual's marginal likelihood which is free from the nuisance mean parameters. The limiting null distributions of the proposed tests are the χ²distributions, and are affected not by the size and the location of breaks but only by the number of breaks.

We set the structural breaks under both the null and the alternative hypotheses to relieve a possible vagueness in interpreting test results in empirical work. The null hypothesis implies a unit root process with level shifts and the alternative connotes a stationary process with level shifts. The Monte Carlo simulation shows that our tests are locally more powerful than the OLSE-based tests, and that the powers of our tests, in a fixed time span, remain stable regardless the number of breaks. In our application, we employ the data which are analyzed by Perron (1990), and some results differ from those of Perron's (1990).     

大学生关于能力与热情的内隐混合性别刻板印象：来自IAT的证据

目的：考察大学生关于能力与热情的内隐混合性别刻板印象。方法：从某高校选取90名大学生,采用两个内隐联想测验（IAT）探讨大学生是否对男女两性存在热情和能力两个内容维度的混合刻板印象。结果：与女性相比,大学生更多地将消极热情和积极能力与男性相联系;与男性相比,被试更多地将积极热情和消极能力与女性相联系。结论：被试对男性存在着消极热情—积极能力的内隐混合性别刻板印象,对女性存在积极热情—消极能力的内隐混合性别刻板印象。     

信息产业对经济增长的效用研究

为量化信息产业对经济增长的作用,通过对投入产出模型进行结构化分解,测算了2007和2012年我国信息产业的乘数效应、反馈效应和溢出效应。结果表明,溢出效应最为显著,这说明信息产业投入越高,对其他产业的贡献也越高。同时,基于2001—2012年29个省份面板数据,采用向量自回归模型和面板Granger因果检验,分析了信息产业对经济增长的效用机制,验证了信息产业对经济增长的直接贡献和间接贡献。结果表明,信息产业和国内生产总值(GDP)之间存在协整关系,信息产业与经济增长双向相关性显著,经济增长是信息产业增长的同质Granger因,各省份GDP以相同的效用机制影响信息产业;信息产业是GDP的异质Granger因,各省份信息产业的增长以不同机制影响GDP增长。     

A simulation study on power comparisons for group sequential tests of non-parametric statistics

In this article, a group sequential test (GST) of non-parametric statistics for survival data is briefly reviewed. An asymptotic joint distribution of the test statistics, obtained after each interim analysis, is given to illustrate the applicability of the critical values of the GST procedures. It should be noted that censored observations are generally seen in survival data. Therefore, if one makes power calculations irrespective of censoring, reliable results may not be achieved, due to the lack of information about the censoring structure. A wide simulation study, covering different censoring rates and tied observations, is conducted to make the power comparisons under various scenarios. The simulation results are interpreted and compared with the results obtained by using power analysis and sample size (PASS) software.     

Measuring non-linear dependence for two random variables distributed along a curve

We propose new dependence measures for two real random variables not necessarily linearly related. Covariance and linear correlation are expressed in terms of principal components and are generalized for variables distributed along a curve. Properties of these measures are discussed. The new measures are estimated using principal curves and are computed for simulated and real data sets. Finally, we present several statistical applications for the new dependence measures.     

A survey of permutation tests for censored survival data

The present paper surveys tests with censored sur-vival data for 2-and k-samples and for association by a framework which classifies them into complete or restric-ted permutation tests and into tests based on U-or Savage-scores. The formulae of the resulting twelve tests are briefly described for quick reference. Some of the tests have been applied frequently in the past as the tests by Mantel, Breslow or Gehan; others have been developed rather recently, partly by the author. The concluding discussion presents the results of a simulation study, clarifying similarities and differences of the restricted and complete permutation approach, and deals with rela-tive efficiencies of the two scoring systems.