“边缘化”大学生个体成因、预防与矫治的研究

＂边缘化＂学生是指行为超出正常规范、学业严重不佳的学生个体。认为中学及大学阶段的管理、社会因素、理想与现实的错位以及个人性格心理特点等是形成＂边缘化＂学生个体的主要原因;管理者建立＂防边缘化＂预警机制、抓住管理的关键时期及努力营造良好学风是有效预防＂边缘化＂的措施;选择适当的角度和有效的工作方法可以对＂边缘化＂学生完成成功矫治。     

Two-tailed asymptotic inferences for a proportion

This paper evaluates 29 methods for obtaining a two-sided confidence interval for a binomial proportion (16 of which are new proposals) and comes to the conclusion that: Wilson's classic method is only optimal for a confidence of 99%, although generally it can be applied when n≥50; for a confidence of 95% or 90%, the optimal method is the one based on the arcsine transformation (when this is applied to the data incremented by 0.5), which behaves in a very similar manner to Jeffreys’ Bayesian method. A simpler option, though not so good as those just mentioned, is the classic-adjusted Wald method of Agresti and Coull.     

Verification bias on sensitivity and specificity measurements in diagnostic medicine: a comparison of some approaches used for correction

Verification bias may occur when the test results of not all subjects are verified by using a gold standard. The correction for this bias can be made using different approaches depending on whether missing gold standard test results are random or not. Some of these approaches with binary test and gold standard results include the correction method by Begg and Greenes, lower and upper limits for diagnostic measurements by Zhou, logistic regression method, multiple imputation method, and neural networks. In this study, all these approaches are compared by employing a real and simulated data under different conditions.     

Estimation of population mean and variance in flock management: a ranked set sampling approach in a finite population setting

Ranked set sampling is a sampling technique that provides substantial cost efficiency in experiments where a quick, inexpensive ranking procedure is available to rank the units prior to formal, expensive and precise measurements. Although the theoretical properties and relative efficiencies of this approach with respect to simple random sampling have been extensively studied in the literature for the infinite population setting, the use of ranked set sampling methods has not yet been explored widely for finite populations. The purpose of this study is to use sheep population data from the Research Farm at Ataturk University, Erzurum, Turkey, to demonstrate the practical benefits of ranked set sampling procedures relative to the more commonly used simple random sampling estimation of the population mean and variance in a finite population. It is shown that the ranked set sample mean remains unbiased for the population mean as is the case for the infinite population, but the variance estimators are unbiased only with use of the finite population correction factor. Both mean and variance estimators provide substantial improvement over their simple random sample counterparts.     

Bias corrected MLEs under progressive type-II censoring scheme

ABSTRACT

Censoring frequently occurs in survival analysis but naturally observed lifetimes are not of a large size. Thus, inferences based on the popular maximum likelihood (ML) estimation which often give biased estimates should be corrected in the sense of bias. Here, we investigate the biases of ML estimates under the progressive type-II censoring scheme (pIIcs). We use a method proposed in Efron and Johnstone [Fisher's information in terms of the hazard rate. Technical Report No. 264, January 1987, Stanford University, Stanford, California; 1987] to derive general expressions for bias corrected ML estimates under the pIIcs. This requires derivation of the Fisher information matrix under the pIIcs. As an application, exact expressions are given for bias corrected ML estimates of the Weibull distribution under the pIIcs. The performance of the bias corrected ML estimates and ML estimates are compared by simulations and a real data application.     

Performance of a bartlett-type modification for the deviance

Cordeiro (1983) has derived the expected value of the deviance for generalized linear models correct to terms of order n ^-1 being the sample size. Then a Bartlett-type factor is available for correcting the first moment of the deviance and for fitting its distribution. If the model is correct, the deviance is not, in general, distributed as chi-squared even asymptotically and very little is known about the adequacy of the X ² approximation. This paper through simulation studies examines the behaviour of the deviance and a Bartlett adjusted deviance for testing the goodness-of-fit of a generalized linear model. The practical use of such adjustment is illustrated for some gamma and Poisson models. It is suggested that the null distribution of the adjusted deviance is better approximated by chi-square than the distribution of the deviance.     

Bias-corrected random forests in regression

It is well known that random forests reduce the variance of the regression predictors compared to a single tree, while leaving the bias unchanged. In many situations, the dominating component in the risk turns out to be the squared bias, which leads to the necessity of bias correction. In this paper, random forests are used to estimate the regression function. Five different methods for estimating bias are proposed and discussed. Simulated and real data are used to study the performance of these methods. Our proposed methods are significantly effective in reducing bias in regression context.     

英语写作教学中的错误反馈研究

引入输入输出假说理论以及错误反馈在L2课堂中的教学意义,讨论了英语写作教学课堂中有关错误反馈的一些重要问题:错误反馈的作用,何时以及如何应用错误反馈。认为错误反馈有助于提高外语学习者的写作水平,而要满足所有教师和学生的要求,仅靠单一的错误反馈方法是不够的。     

电动钻机步进式平移结构应力监测及强度分析

步进式平移可实现钻机前后左右整体移动,具有移动快速、操作便捷的特点,在丛式井组中应用广泛。针对 在役电动钻机加装步进式平移装置后,能否满足满立根情况下钻机整体平移的问题,开展了钻机平移结构应力监测试 验研究,以川庆钻探公司一台ZJ50DBS 钻机为研究对象,通过有限元分析找出钻机平移时结构受力较大部位的应力 监测点,在钻机无立根工况下进行钻机平移应力监测,再在试验数据分析结果基础上,以强度校核结果为目标值,对钻 机结构有限元模型进行修正,最后在修正模型上施加满立根载荷进行钻机整体平移受力分析。分析结果表明,该钻机 在底座安装步进式平移装置后,能够满足在满立根情况下的安全平移。