Goodness-of-Fit Statistics for General Linear Regression Equations in the Presence of Replicated Responses

Goodness-of-fit statistics for general multiple-linear-regression equations are reviewed for the case of replicated responses. A modification of the coefficient of determination is recommended. This statistic has 1.0 as its achievable upper bound and has the coefficient of determination as a special case. It indicates more effectively how close a general-linear-regression equation is relative to the best possible one and is particularly useful when the purpose is to ascertain whether higher-order terms of a given set of explanatory variables are required. Other goodness-of-fit statistics that take into account the variation within replicated responses are reviewed. An illustration example is presented.     

LOWER BOUNDS TO THE POPULATION SIZE WHEN CAPTURE PROBABILITIES VARY OVER INDIVIDUALS

The problem of estimating population sizes has a wide range of applications. Although the size is non-identifiable when a population is heterogeneous, it is often useful to estimate the lower bounds and to construct lower confidence limits. A sequence of lower bounds, including the well-known Chao lower bound, is proposed. The bounds have closed-form expressions and are estimated by the method of moments or by maximum likelihood. Real examples from epidemiology, wildlife management and ecology are investigated. Simulation studies are used to assess the proposed estimators.     

Hypothesis testing for two-group incomplete-data growth curve problems

Using simulation techniques, the null distribution properties of seven hypothesis testing procedures and a comparison of their powers are investigated for incomplete-data small-sample growth curve situations. The testing procedures are a combination of two growth curve models (the Potthoff and Roy model for complete data and Kleinbaum's extention to incomplete data) and three estimation techniques (two involving means of existing observations and the other using the EM algorithm) plus an analysis of a subset of complete data. All of the seven tests use the Kleinbaum Wald statistic, but different tests use different information. The hypotheses of identical and parallel growth curves are tested under the assumptions of multivariate normality and a linear polynomial mean growth curve for each of two groups. Good approximate null distributions are found for all procedures and one procedure is identified as empirically most powerful for the situations investigated.     

Three-factor symmetrical balanced designs with full efficiency for main effects

Some methods for constructing balanced design for 3-factor symmetrical factorial experiments in which all the main effects are completely unconfounded by using balanced arrays and BIB designs are proposed. The method is flexible in terms of selecting block size.     

研究生《机器人系统技术》课程思政建设

相比较本科生群体,研究生的思想政治教育更多来自专业课程的课堂以及导师的言传身教.为此,加强研究生专业课程以及专业课堂的思政建设意义重大.以研究生专业课程《机器人系统技术》专业课为例,从教学目标、教学内容以及教学考核等方面,探讨了思政元素与专业教学如何有机融合,可为同类研究生课程的课堂思政建设提供一定参考.     

基于OBE理念的土力学课程教学改革研究

OBE是以学生取得的学习成果为导向的教育理念,对指导工程教育认证具有较大意义.为提高学生的学习效果,通过丰富教学方法、改进教学手段等,加强虚拟仿真实验建设,将土力学理论与实践应用紧密结合,将现代化教学手段与传统教学方法相结合,使教师不断地提高自身素质,从而激发学生学习兴趣,有助于学生能力的培养和人才培养质量的提高.     

破解OFDI建立模式中的文化距离悖论：注意力的调节作用

建立模式是国际化研究和实践中的重要议题,文化距离是一个备受关注的国家层面因素。然而主流理论框架关于文化距离与建立模式的关系存在着“文化距离悖论”。事实上,文化距离的扩大同时造成内部整合风险和外部适应风险,而新建和并购模式在降低内外部风险方面各有所长。因此,跨国企业对内外风险的注意力分配决定了企业选择新建还是并购的进入方式。实证研究发现：跨国企业本地化战略和东道国市场环境动态性将正向调节文化距离与并购建立模式之间的关系,这一调节作用又会随着企业防御性的提高而增强。     

Partial order relations for classification comparisons

The Bayes classification rule offers the optimal classifier, minimizing the classification error rate, whereas the Neyman–Pearson lemma offers the optimal family of classifiers to maximize the detection rate for any given false alarm rate. These motivate studies on comparing classifiers based on similarities between the classifiers and the optimal. In this article, we define partial order relations on classifiers and families of classifiers, based on rankings of rate function values and rankings of test function values, respectively. Each partial order relation provides a sufficient condition, which yields better classification error rates or better performance on the receiver operating characteristic analysis. Various examples and applications of the partial order theorems are discussed to provide comparisons of classifiers and families of classifiers, including the comparison of cross-validation methods, training data that contains outliers, and labelling errors in training data. The Canadian Journal of Statistics 48: 152–166; 2020 © 2019 Statistical Society of Canada     

The win ratio: Impact of censoring and follow‐up time and use with nonproportional hazards

The win ratio has been studied methodologically and applied in data analysis and in designing clinical trials. Researchers have pointed out that the results depend on follow‐up time and censoring time, which are sometimes used interchangeably. In this article, we distinguish between follow‐up time and censoring time, show theoretically the impact of censoring on the win ratio, and illustrate the impact of follow‐up time. We then point out that, if the treatment has long‐term benefit from a more important but less frequent endpoint (eg, death), the win ratio can show that benefit by following patients longer, avoiding masking by more frequent but less important outcomes, which occurs in conventional time‐to‐first‐event analyses. For the situation of nonproportional hazards, we demonstrate that the win ratio can be a good alternative to methods such as landmark survival rate, restricted mean survival time, and weighted log‐rank tests.     

Penalized full likelihood approach to variable selection for Cox’s regression model under nested case–control sampling

Lifetime Data Analysis - Assuming Cox’s regression model, we consider penalized full likelihood approach to conduct variable selection under nested case–control (NCC) sampling....