Corrected f-tests in the general linear model

The theory of corrected F-tests in the general linear modeL with correlated errors is studied in this paper. Strictly unbiased F-tests are constructed in the presence of a large class of known non-identity correlation structures. These are generalized likelihood ratio tests which are easily computed. Critical points from the standard F-tables can be used to provide an exact test of desired size.     

Statistical Artifacts in the Ratio of Discrete Quantities

The ratio is a familiar statistic, but it is often misused. One frequently overlooked problem occurs when ratioing two discrete (digitized) variables. Fine structure appears in the histogram of the ratio that can be very subtle, or can sometimes even dominate the histogram. It disappears when the numerator and/or denominator become continuous. This statistical artifact is not a binning error, nor is it removed by taking more data. It is important to be aware of the artifact in order to avoid misinterpretation of ratio data. We provide examples of the statistical artifact (including one from baseball) and discuss ways to avoid or minimize the problems it can cause.     

Analysis of mixed outcomes: misclassified binary responses and measurement error in covariates

This paper considers regression models for mixed binary and continuous outcomes, when the true predictor is measured with error and the binary responses are subject to classification errors. The focus of the paper is to study the effects of these errors on the estimates of the model parameters and also to propose a model that incorporates both these errors. The proposed model results in a substantial improvement in the estimates as shown by extensive simulation studies.     

The widespread misinterpretation of p-values as error probabilities

The anonymous mixing of Fisherian (p-values) and Neyman–Pearsonian (α levels) ideas about testing, distilled in the customary but misleading p < α criterion of statistical significance, has led researchers in the social and management sciences (and elsewhere) to commonly misinterpret the p-value as a ‘data-adjusted’ Type I error rate. Evidence substantiating this claim is provided from a number of fronts, including comments by statisticians, articles judging the value of significance testing, textbooks, surveys of scholars, and the statistical reporting behaviours of applied researchers. That many investigators do not know the difference between p’s and α’s indicates much bewilderment over what those most ardently sought research outcomes—statistically significant results—means. Statisticians can play a leading role in clearing this confusion. A good starting point would be to abolish the p < α criterion of statistical significance.     

对外汉语语音教学中声母教学研究

对外汉语教学中,语音教学贯穿汉语教学的初级阶段,对今后的学习至关重要。但由于受母语负牵移的影响,常常存在发音偏误。着重探讨声母教学中外国学生易出现的偏误及对策。     

毛泽东在商品经济问题上步入误区的思想渊源探析

社会主义时期,毛泽东对商品经济时而肯定,时而否定,并最终走向否定,步入误区.造成这种状况的原因是极其复杂的,但从根本上讲,与毛泽东所接受的马恩关于社会主义社会的设想及中国传统文化中平均主义和大同思想的影响有密切关系.深入探究这一问题,将有助于我们加深对邓小平社会主义市场经济理论的认识和理解.     

Misogyny in New York custody decisions with parental alienation and child sexual abuse allegations

This article analyzes 24 New York (NY) published child custody cases decided between 2001 and 2017 that contained parental alienation and child sexual allegations. It addresses whether there was a tendency toward gendered decisions and the evidence on which the decisions were based. It reveals that most decisions favored alienation allegations over child sexual abuse allegations and transferring custody from mothers communicating sexual abuse allegations in court to fathers defending against them by alleging parental alienation. On appeal, these family court decisions were overwhelmingly upheld. The analysis also shows that the decisions were based as often on implicit misogynistic cultural assumptions in the absence of allegation-specific evidence as they were on allegation-specific evidence. The article adds to the growing understanding of sources of bias by proposing four errors that support biased reasoning. It concludes with suggestions about how experts, attorneys, and judges can question themselves and others to reduce bias.     

Consistent estimation approach to tackling collinearity and Berkson-type measurement error in linear regression using adjusted Wald-type estimator

This article proposes a consistent estimation approach in linear regression models for the case when the predictor variables are subject to collinearities and Berkson-type measurement errors simultaneously. Our presented procedure does not rely on ridge regression (RR) methods that have been widely addressed in the literature for ill-conditioned problems resulted from multicollinearity. Instead, we review and propose new consistent estimators due to Wald (1940 Wald, A. (1940). Fitting of straight lines if both variables are subject to error. Ann. Math. Stat. 11:284–300.[Crossref] , [Google Scholar]) so that, except finite fourth moments assumptions, no prior knowledge of parametric settings on observations and errors is used, and there is no need to solve estimating equations for coefficient parameters. The performance of the estimation procedure is compared with that of RR-based estimators by using a variety of numerical experiments through Monte Carlo simulation under estimated mean squared error (EMSE) criterion.     

Statistical monitoring of a web server for error rates: a bivariate time-series copula-based modeling approach

The monitoring of web servers through statistical frameworks is of utmost important in order to verify possible suspicious anomalies in network traffic or misuse actions that compromise integrity, confidentiality, and availability of information. In this paper, by considering the Plackett copula function, we propose a bivariate beta-autoregressive moving average time-series model for proportion data over time, which is the case for variables present in web server monitoring such as error rates. To illustrate the proposed methodology, we monitor a Brazilian web server's rate of connection synchronization and rejection errors in a web system, with error logging rate in the past 10?min. In essence, the entire methodology may be generalized to any number of time-series of error rates.