“四史”教育融入高校思政课教学的五维逻辑进路

历史照亮过去，历史启迪未来。以党史、新中国史、改革开放史、社会主义发展史为核心内容的“四史”教育，是以历史为基础的思想政治教育。从党史、新中国史、改革开放史、社会主义发展史中挖掘思想政治理论课教育资源，对高校传承红色基因、落实立德树人根本任务具有重要的指导意义。以庆祝中国共产党成立100周年为契机，将“四史”教育融入高校思想政治理论课教学，必须遵循相应的逻辑理路：树立正确党史观、坚定理想信念的价值追求是融入的逻辑立场；强化大历史观、理解党的伟大贡献是融入的逻辑方法；坚持内在统一性、把握“四史”教育的整体性逻辑是融入的基本前提；抓住侧重点、精准对接各门大学生思想政治理论课程是融入的逻辑核心；坚持实践逻辑、引导大学生从“四史”中汲取智慧和力量是融入的根本遵循。     

Tests for homogeneity of risk differences in stratified design with correlated bilateral data

ABSTRACT

Correlated bilateral data arise from stratified studies involving paired body organs in a subject. When it is desirable to conduct inference on the scale of risk difference, one needs first to assess the assumption of homogeneity in risk differences across strata. For testing homogeneity of risk differences, we herein propose eight methods derived respectively from weighted-least-squares (WLS), the Mantel-Haenszel (MH) estimator, the WLS method in combination with inverse hyperbolic tangent transformation, and the test statistics based on their log-transformation, the modified Score test statistic and Likelihood ratio test statistic. Simulation results showed that four of the tests perform well in general, with the tests based on the WLS method and inverse hyperbolic tangent transformation always performing satisfactorily even under small sample size designs. The methods are illustrated with a dataset.     

Revisiting Nested Group Testing Procedures: New Results,Comparisons, and Robustness

Group testing has its origin in the identification of syphilis in the U.S. army during World War II. Much of the theoretical framework of group testing was developed starting in the late 1950s, with continued work into the 1990s. Recently, with the advent of new laboratory and genetic technologies, there has been an increasing interest in group testing designs for cost saving purposes. In this article, we compare different nested designs, including Dorfman, Sterrett and an optimal nested procedure obtained through dynamic programming. To elucidate these comparisons, we develop closed-form expressions for the optimal Sterrett procedure and provide a concise review of the prior literature for other commonly used procedures. We consider designs where the prevalence of disease is known as well as investigate the robustness of these procedures, when it is incorrectly assumed. This article provides a technical presentation that will be of interest to researchers as well as from a pedagogical perspective. Supplementary material for this article is available online.     

大数据时代项目评审中社会伦理问题的对抗性设计

通过对抗性设计方法解决项目评审中的社会伦理问题，为专家、申请者、大众提供争论和表达异议的民主环境。项目自动评价平台完成民主环境的构建，呈现专家、申请者、平台的争胜性关系，揭示霸权，旨在重塑自由、平等、公平、正义、特权等的项目评审中的社会伦理。     

Regression analysis of case-cohort studies in the presence of dependent interval censoring

The case-cohort design is widely used as a means of reducing the cost in large cohort studies, especially when the disease rate is low and covariate measurements may be expensive, and has been discussed by many authors. In this paper, we discuss regression analysis of case-cohort studies that produce interval-censored failure time with dependent censoring, a situation for which there does not seem to exist an established approach. For inference, a sieve inverse probability weighting estimation procedure is developed with the use of Bernstein polynomials to approximate the unknown baseline cumulative hazard functions. The proposed estimators are shown to be consistent and the asymptotic normality of the resulting regression parameter estimators is established. A simulation study is conducted to assess the finite sample properties of the proposed approach and indicates that it works well in practical situations. The proposed method is applied to an HIV/AIDS case-cohort study that motivated this investigation.     

Designing Graphs that Promote Both Risk Understanding and Behavior Change

Graphs show promise for improving communications about different types of risks, including health risks, financial risks, and climate risks. However, graph designs that are effective at meeting one important risk communication goal (promoting risk‐avoidant behaviors) can at the same time compromise another key goal (improving risk understanding). We developed and tested simple bar graphs aimed at accomplishing these two goals simultaneously. We manipulated two design features in graphs, namely, whether graphs depicted the number of people affected by a risk and those at risk of harm (“foreground+background”) versus only those affected (“foreground‐only”), and the presence versus absence of simple numerical labels above bars. Foreground‐only displays were associated with larger risk perceptions and risk‐avoidant behavior (i.e., willingness to take a drug for heart attack prevention) than foreground+background displays, regardless of the presence of labels. Foreground‐only graphs also hindered risk understanding when labels were not present. However, the presence of labels significantly improved understanding, eliminating the detrimental effect of foreground‐only displays. Labels also led to more positive user evaluations of the graphs, but did not affect risk‐avoidant behavior. Using process modeling we identified mediators (risk perceptions, understanding, user evaluations) that explained the effect of display type on risk‐avoidant behavior. Our findings contribute new evidence to the graph design literature: unlike what was previously feared, we demonstrate that it is possible to design foreground‐only graphs that promote intentions for behavior change without a detrimental effect on risk understanding. Implications for the design of graphical risk communications and decision support are discussed.     

Economic statistical design of the T2 control chart under the Weibull shock model with multiple assignable causes

A proper monitoring of stochastic systems is the control charts of statistical process control and drift in characteristics of output may be due to one or several assignable causes. Although much research has been done on the design of control charts, the economic statistical design of the T2 control chart under the Weibull shock model with multiple assignable causes has not yet been addressed. Therefore, we tried to deal with it in this paper and thus we developed a cost model based on the variable sampling interval. We also give an example to support the practical use of T2 chart under the Weibull shock model with multiple assignable causes. Based on the optimization of the average cost per unit of time and taking into account the different combination values of Weibull distribution parameters, optimal values of design parameters were derived and calculated. Then, the cost models under the influence of single assignable cause and multiple assignable causes under the same cost and time parameters were compared. Also, a sensitivity analysis was conducted in which the variability of loss cost and design parameters due to change of cost and time and Weibull distribution parameters were evaluated.     

中国古代墓志形制变迁中的设计思想内蕴

以中国历代墓志形制与文体变化为纵向轴，一是以魏晋南北朝中的“志”“碑”合一形式以及宋齐梁陈中出现的简单化的墓志形式，论述了中国古代墓志设计的“实用”思想；二是以历代墓志文体演变为研读对象，系统论述了墓志文体设计演变中的“实用”与“浮华”的转变。系统考察中国历代墓志的形制与文体设计，墓志作为随葬风俗的一部分，其形制变化基本轨迹还是以实用为美、为尚。浮华的特质在重葬、经济允许的情况下，尤其是墓志志文成为文化人施展才华的载体之际，文体适应了为死者“歌颂”的普世之需，同时也体现了设计“应需而变”的设计本质。     

A Shiny Update to an Old Experiment Game

ABSTRACT

Games can be a powerful tool for learning about statistical methodology. Effective game design involves a fine balance between caricature and realism, to simultaneously illustrate salient concepts in a controlled setting and serve as a testament to real-world applicability. Striking that balance is particularly challenging in response surface and design domains, where real-world scenarios often play out over long time scales, during which theories are revised, model and inferential techniques are improved, and knowledge is updated. Here, I present a game, borrowing liberally from one first played over 40 years ago, which attempts to achieve that balance while reinforcing a cascade of topics in modern nonparametric response surfaces, sequential design, and optimization. The game embeds a blackbox simulation within a shiny app whose interface is designed to simulate a realistic information–availability setting, while offering a stimulating, competitive environment wherein students can try out new methodology, and ultimately appreciate its power and limitations. Interface, rules, timing with course material, and evaluation are described, along with a “case study” involving a cohort of students at Virginia Tech. Supplementary materials for this article are available online.     

Methodological considerations in the use of name generators and interpreters

With data from the Clergy Health Initiative Longitudinal Survey, we look for interviewer effects, differences between web and telephone delivery, and panel conditioning bias in an “important matters” name generator and interpreter, replicated from the U.S. General Social Survey. We find evidence of phone interviewers systematically influencing the number of confidants named, we observe that respondents assigned to the web survey reported a larger number of confidants, and we uncover strong support for panel conditioning. We discuss the possible mechanisms behind these observations and conclude with a brief discussion of the implications of our findings for similar studies.