Properties of a distribution-free two-stage two-sample median test

Abstract  In this paper we consider a class of distribution-free two-stage two-sample median tests. These procedures are based on a fixed size sample from one population, while the observations from the second population are collected in a truncated sequential fashion. Necessary tables are provided enabling us to select a particular member from the class such that arbitrarily preset power levels are approximately obtained. We also present asymptotic expressions and tables for the expected number of observations from the second population. Finally, comparisons between the asymptotic version of this two-stage median test and the binomial sequential probability ratio test due to W ald (1947) are discussed.     

Asymptotic expansion of the power function of the two-sample binomial test with and without randomization

The paper deals with the asymptotic expansion of the power function of the two-sample binomial test. This test is a conditional test which is based upon the hypergeometric distribution, and we consider both the version with and without randomization. First, we give the asymptotic expansion of the hypergeometric distribution function and of its quantiles including randomization weights. Then we describe the asymptotic expansions of the power function of the two test versions and discuss the results.     

Asymptotic power of the two-sample test of Wilcoxon for Logistic shift alternatives, and comparison with simulation results

In this paper the power of the two-sample test of W ilcoxon for Logistic shift alternatives is computed by using two approximations, based on the asymptotic Normality of the test statistic. The sample sizes considered are m = n = 6, m = n= 10 and m = n = 15 . These approximations are compared with the results of an experimental determination by Monte Carlo techniques.     

Exact distribution of Durbin's distribution-free test statistic for Balanced Incomplete Block Designs, and comparison with the Chi-square and F approximation

Durbin's distribution-free rank test can be used to test the null hypothesis that there are no differences among the treatments in a Balanced Incomplete Block Design. Until now only the chi-square and F approximations for the test statistic were known. In this paper the exact distribution has been given for 15 designs and comparison is made with the chi-square and F approximation.     

A sequential procedure to test three values of a binomial parameter

Sequential tests to decide among three binomial probabilities are needed in many situations, such as acceptance sampling used to determine the proportion of defective items and presence and absence sampling to decide whether pest species are causing economic damage to a crop such as corn. Approximate error probabilities associated with Armitage's (1950, JRSS B) method of simultaneously conducting three sequential probability ratio tests (SPRTs) are derived for the binomial distribution. These approximations provide a basis for adjusting the error rates used to establish the individual SPRTs so that the desired overall error rates are attained. Monte Carlo simulation is used to evaluate the revised procedure. Received: September 1998     

The effect of applicant race upon personnel selection decisions: A review with recommendations

The research literature addressed in this review concerns unfair racial discrimination in the personnel selection process. Because of methodological limitations and narrow research interests, the extant research fails to provide a clear framework from which to interpret the impact of racial discrimination on personnel selection, nor does it adequately account and control for the factors associated with unfair racial discrimination. Furthermore, this report shows that investigations concerning racial minorities other than blacks are virtually nonexistent. Following reviews of resume, in-basket, and interviewing studies, recommendations for future research are provided.     

单整变量之间Granger因果关系的一种检验程序

本文系统研究了含有单整变量的变量之间Granger因果关系基于OLS估计的检验方法,将适用于存在（1,1）阶协整关系的I(1)变量之间Granger因果关系检验的Engle和Granger（1987）两步程序,扩展到了存在协整关系的高阶单整变量的情形,并提出了含有单整变量的变量之间Granger因果关系检验的一般程序。     

A comparison of several approximations to the power function of the likelihood ratio test in covariance structure analysis*

In this paper we compare alternative asymptotic approximations to the power of the likelihood ratio test used in covariance structure analysis for testing the fit of a model. Alternative expressions for the noncentrality parameter (ncp) lead to different approximations to the power function. It appears that for alternative covariance matrices close to the null hypothesis, the alternative ncp's lead to similar values, while for alternative covariance matrices far from H_o the different expressions for the ncp can conflict substantively. Monte Carlo evidence shows that the ncp proposed in Satorra and Saris (1985) gives the most accurate power approximations.     

四向可调式转向管柱三段溃缩结构设计与试验

为了降低汽车碰撞过程中转向系统对驾驶员伤害程度,文章提出一种四向可调式转向管柱的溃缩装置,该装置设计了3个吸能结构,在碰撞溃缩整个过程中分为3个阶段,每个阶段独立且较为明晰,结合C-NCAP管理规则对转向管柱的溃缩要求获得了详细的溃缩曲线,将该转向管柱应用到国内某款轿车中,在C-NAP试验过程中取得良好的效果。     

A simple test for regression specification with non-nested alternatives

In this paper, I introduce a simple test for the presence of the data-generating process among several non-nested alternatives. The test is an extension of the classical J test for non-nested regression models. I also provide a bootstrap version of the test that avoids possible size distortions inherited from the J test.     

A Simple Test for Cointegration in Dependent Panels with Structural Breaks*

This paper develops a very simple test for the null hypothesis of no cointegration in panel data. The test is general enough to allow for heteroskedastic and serially correlated errors, unit‐specific time trends, cross‐sectional dependence and unknown structural breaks in both the intercept and slope of the cointegrated regression, which may be located at different dates for different units. The limiting distribution of the test is derived, and is found to be normal and free of nuisance parameters under the null. A small simulation study is also conducted to investigate the small‐sample properties of the test. In our empirical application, we provide new evidence concerning the purchasing power parity hypothesis.     

Estimating Nonlinear Models with Multiple Fixed Effects: A Computational Note*

In this paper we consider estimation of nonlinear panel data models that include multiple individual fixed effects. Estimation of these models is complicated both by the difficulty of estimating models with possibly thousands of coefficients and also by the incidental parameters problem; that is, noisy estimates of the fixed effects when the time dimension is short contaminate the estimates of the common parameters due to the nonlinearity of the problem. We propose a simple variation of existing bias‐corrected estimators, which can exploit the additivity of the effects for numerical optimization. We exhibit the performance of the estimators in simulations.     

Toggling with Taylor: A Different Approach to Reading a Management Text*

ABSTRACT This paper identifies influential, but previously unrecognized, subtexts in the writings of Frederick Winslow Taylor. Working with analytical methods developed from reader‐response theories of literary criticism, we look at the words of the text as we share the standard meaning‐making of the management community, as well as through the words of the text searching out the worldview that emerges from our particular reading of the subtext. We have described our approach to reading as ‘toggling’: that is, switching between reading text ‘rhetorically’ and reading it ‘philosophically’. We conclude that reader identification with textual voices may appear in philosophical as well as rhetorical reading outcomes – that Taylor's text may inveigle readers into accepting a moral worldview wrapped up in a seemingly rational argument – and that ‘toggling’ would empower management theory readers.     

A consistent model specification test with mixed discrete and continuous data

In this paper we propose a nonparametric kernel-based model specification test that can be used when the regression model contains both discrete and continuous regressors. We employ discrete variable kernel functions and we smooth both the discrete and continuous regressors using least squares cross-validation (CV) methods. The test statistic is shown to have an asymptotic normal null distribution. We also prove the validity of using the wild bootstrap method to approximate the null distribution of the test statistic, the bootstrap being our preferred method for obtaining the null distribution in practice. Simulations show that the proposed test has significant power advantages over conventional kernel tests which rely upon frequency-based nonparametric estimators that require sample splitting to handle the presence of discrete regressors.     

A new fluctuation test for constant variances with applications to finance

We present a test to determine whether variances of time series are constant over time. The test statistic is a suitably standardized maximum of cumulative first and second moments. We apply the test to time series of various assets and find that the test performs well in applications. Moreover, we propose a portfolio strategy based on our test which hedges against potential financial crises and show that it works in practice.     

A test of goodness-of-fit based on extreme spacings with some efficiency comparisons

Tests for the goodness-of-fit problem based on sample spacings, i.e., observed distances between successive order statistics, have been used in the literature. We propose a new test based on the number of “small” and “large” spacings. The asymptotic theory under close alternative sequences is also given thus enabling one to calculate the asymptotic relative efficiencies of such tests. A comparison of the new test and other spacings tests is given.     

A test for multimodality of regression derivatives with application to nonparametric growth regressions

This paper presents a method to test for multimodality of an estimated kernel density of derivative estimates from a nonparametric regression. The test is included in a study of nonparametric growth regressions. The results show that in the estimation of unconditional β‐convergence the distribution of the partial effects is multimodal, with one mode in the negative region (primarily OECD economies) and possibly two modes in the positive region (primarily non‐OECD economies) of the estimates. The results for conditional β‐convergence show that the density is predominantly negative and there is mixed evidence that the distribution is unimodal. Copyright © 2009 John Wiley & Sons, Ltd.     

A nonparametric test for equality of distributions with mixed categorical and continuous data

In this paper we consider the problem of testing for equality of two density or two conditional density functions defined over mixed discrete and continuous variables. We smooth both the discrete and continuous variables, with the smoothing parameters chosen via least-squares cross-validation. The test statistics are shown to have (asymptotic) normal null distributions. However, we advocate the use of bootstrap methods in order to better approximate their null distribution in finite-sample settings and we provide asymptotic validity of the proposed bootstrap method. Simulations show that the proposed tests have better power than both conventional frequency-based tests and smoothing tests based on ad hoc smoothing parameter selection, while a demonstrative empirical application to the joint distribution of earnings and educational attainment underscores the utility of the proposed approach in mixed data settings.     

A generalized nonlinear IV unit root test for panel data with cross-sectional dependence

This paper proposes a unit root test for panel data with cross-sectional dependence. The test generalizes the nonlinear IV unit root test of Chang (2002) to the case where there exist some common factors in panels. The main idea is to eliminate the cross-sectional dependence through the method of principal components as in Bai and Ng (2004) and then apply Chang’s test to the treated data. Under certain conditions, the proposed test is consistent and has a standard normal limiting distribution under the null hypothesis. Simulation results show that the proposed test compares favorably to other alternative tests.