Half-sample variance estimation

This paper studies an alternative to the jackknife variance estimator, the half-sample variance estimator. Both theoretical and Monte Carlo comparisons between the half-sample variance estimator and the jackknife variance estimator indicate that the former is better in some situations.     

Domestic Abuse Assessment in Child Custody Disputes: Beware the Domestic Violence Research Paradigm

ABSTRACT

In some states, custody assessors are now required to become familiar with the dynamics of prevalence of domestic abuse since the presence of one or more abusive parents in the house has an impact on the “best interests of the child.” The domestic abuse literature is misleading in setting a framework for abuse incidence and threat source for children. Males are represented as primary perpetrators of physical abuse although data from meta-analytic studies show otherwise. Indirect aggression is scarcely mentioned in the literature, although prevalent in research on aggression. Physical violence directed towards children is actually more likely to be mother-perpetrated. Child safety may be compromised if attention is focused solely on the possibility of abuse from a male perpetrator.     

Asymptotic robustness of least median of squares for autoregressions with additive outliers

This paper considers the robustness properties in the time series context of the least median of squares (LMS) estimator. The influence function of the LMS estimator is derived under additive outlier contamination. This influence function is redescending and bounded for fixed values of the AR parameters. The gross-error sensitivity, however, is an unbounded function of the AR parameters. In order to asses the global robustness behavior of the LMS estimator, we consider several notions of breakdown. The breakdown points of the LMS estimator depend on the value of the underlying AR parameter. Generally, the breakdown point is below one half for high values of the AR parameter. The bias curves of the LMS estimator reveal, however, that the magnitude of outliers has to be considerable in order to cause breakdown.     

Underestimating busyness: Indications of nonresponse bias due to work-family conflict and time pressure

International research shows that both work-family conflict and time pressure are increasing in Western societies. With these increased pressures, precisely those people who are combining work and family obligations may be missing from survey estimates. This study investigates whether the measurement of work-family conflict (WFC) and time pressure is influenced by nonresponse bias. Using the Flemish “Work, Family and Time use in Flanders”-survey and the Basic Question survey for nonrespondents of this survey, we investigate whether nonrespondents score higher on subjective and objective indicators of WFC and time pressure than respondents. Results show that nonrespondents are indeed those sample units who experience significantly more WFC and time pressure, demonstrating that WFC and time pressure related nonresponse biases exist. Implications and suggestions to reduce bias in data collections are discussed.     

如何充分发挥高校工会在师德建设中的作用研究

如何加强师德建是高校工会工作的一项重要课题，也是体现工会服从于教育改革发展大局的一项重要工作。高校工会应在通过各种途径，协调学校相关部门开展师德建设中发挥应有的作用。     

论教师道德的底线

在人类道德发展史上,教师道德无论是从职业行为规范方面还是在个人道德修养上始终被认为应处于社会的最高水准,代表着社会道德修养的最高层次。教师道德在追求崇高的价值目标的同时,更要坚守教师道德的底线。教师道德的底线是教师职业活动中必须坚守的最低的道德要求。教师与学生的关系是教师道德所调节的伦理关系中最根本、核心的利益关系,相对于教师的利益,学生的利益具有道德上的优先性,学生利益的优先性就决定了教师道德的底线是,教师在任何时候都不能够损害学生的正当合法利益。     

Transformation and Smoothing in Sample Survey Data

Abstract. We consider model‐based prediction of a finite population total when a monotone transformation of the survey variable makes it appropriate to assume additive, homoscedastic errors. As the transformation to achieve this does not necessarily simultaneously produce an easily parameterized mean function, we assume only that the mean is a smooth function of the auxiliary variable and estimate it non‐parametrically. The back transformation of predictions obtained on the transformed scale introduces bias which we remove using smearing. We obtain an asymptotic expansion for the prediction error which shows that prediction bias is asymptotically negligible and the prediction mean‐squared error (MSE) using a non‐parametric model remains in the same order as when a parametric model is adopted. The expansion also shows the effect of smearing on the prediction MSE and can be used to compute the asymptotic prediction MSE. We propose a model‐based bootstrap estimate of the prediction MSE. The predictor produces competitive results in terms of bias and prediction MSE in a simulation study, and performs well on a population constructed from an Australian farm survey.     

近五年教师职业道德研究综述

教师职业道德的研究目前呈现多元化发展趋势,主要集中在教师职业道德内涵及要求、职业道德建设和职业道德评价等方面。梳理国内外研究成果,结果表明,教师职业道德责任包括教师使命和学生权利两个部分,教师是学生的道德榜样,应建立道德守则来规范教师的道德行为,科学评价教师职业道德,进一步丰富教师职业道德的研究内容,拓宽领域,使理论研究与实践研究紧密结合。     

Equality of two blues and ridge-type estimates

Equality is shown of the g-inverse and Moore-Penrose inverse representation of the BLUE in the general linear model. The proof is based on a matrix identity which allows also to establish a functional relationship between the BLUE and Ridge-type estimates.     

Estimation of a discriminant function from a mixture of two inverse Weibull distributions

The classification of a random variable based on a mixture can be meaningfully discussed only if the class of all finite mixtures is identifiable. In this paper, we find the maximum-likelihood estimates of the parameters of the mixture of two inverse Weibull distributions by using classified and unclassified observations. Next, we estimate the nonlinear discriminant function of the underlying model. Also, we calculate the total probabilities of misclassification as well as the percentage bias. In addition, we investigate the performance of all results through a series of simulation experiments by means of relative efficiencies. Finally, we analyse some simulated and real data sets through the findings of the paper.