Translating cross-lagged effects into incidence rates and risk ratios: The case of psychosocial safety climate and depression

Longitudinal studies are the gold standard of empirical work and stress research whenever experiments are not plausible. Frequently, scales are used to assess risk factors and their consequences, and cross-lagged effects are estimated to determine possible risks. Methods to translate cross-lagged effects into risk ratios to facilitate risk assessment do not yet exist, which creates a divide between psychological and epidemiological work stress research. The aim of the present paper is to demonstrate how cross-lagged effects can be used to assess the risk ratio of different levels of psychosocial safety climate (PSC) in organisations, an important psychosocial risk for the development of depression. We used available longitudinal evidence from the Australian Workplace Barometer (N?=?1905) to estimate cross-lagged effects of PSC on depression. We applied continuous time modelling to obtain time-scalable cross effects. These were further investigated in a 4-year Monte Carlo simulation, which translated them into 4-year incident rates. Incident rates were determined by relying on clinically relevant 2-year periods of depression. We suggest a critical value of PSC?=?26 (corresponding to ?1.4 SD), which is indicative of more than 100% increased incidents of persistent depressive disorder in 4-year periods compared to average levels of PSC across 4 years.     

Properties of the weighted log‐rank test in the design of confirmatory studies with delayed effects

Proportional hazards are a common assumption when designing confirmatory clinical trials in oncology. This assumption not only affects the analysis part but also the sample size calculation. The presence of delayed effects causes a change in the hazard ratio while the trial is ongoing since at the beginning we do not observe any difference between treatment arms, and after some unknown time point, the differences between treatment arms will start to appear. Hence, the proportional hazards assumption no longer holds, and both sample size calculation and analysis methods to be used should be reconsidered. The weighted log‐rank test allows a weighting for early, middle, and late differences through the Fleming and Harrington class of weights and is proven to be more efficient when the proportional hazards assumption does not hold. The Fleming and Harrington class of weights, along with the estimated delay, can be incorporated into the sample size calculation in order to maintain the desired power once the treatment arm differences start to appear. In this article, we explore the impact of delayed effects in group sequential and adaptive group sequential designs and make an empirical evaluation in terms of power and type‐I error rate of the of the weighted log‐rank test in a simulated scenario with fixed values of the Fleming and Harrington class of weights. We also give some practical recommendations regarding which methodology should be used in the presence of delayed effects depending on certain characteristics of the trial.     

汇率货币模型的非线性协整关系检验——基于深度GRU神经网络

本文采用深度门控循环单元（GRU）神经网络探讨三种汇率货币模型（弹性价格、前瞻性和实际利率差模型）的非线性协整关系。GRU技术在深度学习中具有智能记忆、自主学习和强逼近能力等优点。为此，本文运用该技术对6组典型浮动汇率制国别数据进行了非线性Johansen协整检验。结果表明，汇率与宏观经济基本面之间存在非线性协整关系，从而说明了货币模型在非线性条件下的有效性，以及先进的深度学习工具在检验经济理论中的优势。     

用联想神经网络设计的信道均衡器

研究了联想神经网络在数字通信信道均衡器实现中的应用,讨论了其设计方法和设计步骤,给出了计算机模拟结果,并进行了性能比较。研究结果表明:Hopfield联想神经网络实现的信道均衡器具有比传统线性横向均衡器更优越的性能。     

ELAN网络控制系统通信处理时间的测量与分析

针对ELAN嵌入式网络微机控制系统中的实时性问题，给出了ELAN网络系统中的通信处理时间的测量方法，并对网络中的通信处理时间进行了分析，最后提出了代码下装的方法。     

关于高校办公室网络化管理的思考

随着科学技术和高等教育的发展,网络也广泛运用于高校办公室的管理工作,并在其中起着重要的作用。     

构建现代远程开放教育考试体系初探

现代远程开放教育是基于以学习者为中心的开放学习和个别化学习。我们应从素质教育的培养目标出发 ,依据现代考试测量理论 ,利用现代科技手段 ,建立现代远程开放教育考试体系 ,客观、准确地评价学习者的进步状况以及在学识、能力等方面达到的水平 ,使学习者在学习过程中不断自我完善 ,培养他们积极进取的精神     

互联网时代的信息传播悖论

互联网上存在这样一个悖论——一方面是海量信息 ,另一方面却是垃圾信息 ,有用信息难以查找 ,文章分析了这一现象产生的原因及其对网络生态环境的危害 ,并初步提出了解决方法。     

Using local linear kernel smoothers to test the lack of fit of nonlinear regression models

Herein, we propose a data-driven test that assesses the lack of fit of nonlinear regression models. The comparison of local linear kernel and parametric fits is the basis of this test, and specific boundary-corrected kernels are not needed at the boundary when local linear fitting is used. Under the parametric null model, the asymptotically optimal bandwidth can be used for bandwidth selection. This selection method leads to the data-driven test that has a limiting normal distribution under the null hypothesis and is consistent against any fixed alternative. The finite-sample property of the proposed data-driven test is illustrated, and the power of the test is compared with that of some existing tests via simulation studies. We illustrate the practicality of the proposed test by using two data sets.     

网络媒体与网络新闻传播

随着网络媒体的出现 ,新闻传播发生了深刻的变革 ,一场借助网络平台进行传播竞争的局面正在形成。网络传播的优势何在 ,如何实现网络新闻传播 ,以及传播环节技术如何运用 ,文章对此进行了探讨。