Random Effects Misspecification Can Have Severe Consequences for Random Effects Inference in Linear Mixed Models

There has been considerable and controversial research over the past two decades into how successfully random effects misspecification in mixed models (i.e. assuming normality for the random effects when the true distribution is non‐normal) can be diagnosed and what its impacts are on estimation and inference. However, much of this research has focused on fixed effects inference in generalised linear mixed models. In this article, motivated by the increasing number of applications of mixed models where interest is on the variance components, we study the effects of random effects misspecification on random effects inference in linear mixed models, for which there is considerably less literature. Our findings are surprising and contrary to general belief: for point estimation, maximum likelihood estimation of the variance components under misspecification is consistent, although in finite samples, both the bias and mean squared error can be substantial. For inference, we show through theory and simulation that under misspecification, standard likelihood ratio tests of truly non‐zero variance components can suffer from severely inflated type I errors, and confidence intervals for the variance components can exhibit considerable under coverage. Furthermore, neither of these problems vanish asymptotically with increasing the number of clusters or cluster size. These results have major implications for random effects inference, especially if the true random effects distribution is heavier tailed than the normal. Fortunately, simple graphical and goodness‐of‐fit measures of the random effects predictions appear to have reasonable power at detecting misspecification. We apply linear mixed models to a survey of more than 4 000 high school students within 100 schools and analyse how mathematics achievement scores vary with student attributes and across different schools. The application demonstrates the sensitivity of mixed model inference to the true but unknown random effects distribution.     

浅析光纤测试技术技巧

光纤的传输速度快,对信号的输入输出起着重要的作用。在光纤布线中,信号衰减不可避免,加上其它不可知因素都对光纤测试带来很大难度。文中就光纤测试技术技巧方面展开探讨。     

风险价值及压力测试在采购策略中的应用

首先分析了供应链采购风险管理的重要性,然后分别介绍了VaR和压力测试这两种风险测度方法,并在此基础上建立了采购风险度量模型,为制定科学的采购策略提供了量化的决策依据。     

Understanding machine learning-based forecasting methods: A decomposition framework and research opportunities

Machine learning (ML) methods are gaining popularity in the forecasting field, as they have shown strong empirical performance in the recent M4 and M5 competitions, as well as in several Kaggle competitions. However, understanding why and how these methods work well for forecasting is still at a very early stage, partly due to their complexity. In this paper, I present a framework for regression-based ML that provides researchers with a common language and abstraction to aid in their study. To demonstrate the utility of the framework, I show how it can be used to map and compare ML methods used in the M5 Uncertainty competition. I then describe how the framework can be used together with ablation testing to systematically study their performance. Lastly, I use the framework to provide an overview of the solution space in regression-based ML forecasting, identifying areas for further research.     

物资质量检验在物资流通中的作用

现代社会经济活动中,社会分工越来越细微,作为流通领域中的一个重要环节,物流正发挥着越来越重要的作用,同时,也对物流工作中的物资质量检验提出了更高的要求,做好物资质量检验不仅仅对物流管理至关重要,而且关系到社会经济的健康发展。     

大唐克旗#3机组电气整套启动试验危险点分析

发电机组的电气整套试验是一种综合性试验,主要包括发变组短路试验、发变组空载试验、励磁系统试验、同期系统试验等试验项目。在整个电气整套试验的过程中,该机组存在着一些可能导致机组试验失败和人身设备安全的危险点,通过对这些危险点的分析处理,可以为其他试运机组出现同类现象提供借鉴和参考。     

半导体照明产品检测实验室建设及展望

基于半导体照明灯具的特点,结合目前半导体照明产品检测的实际情况,从光、色、电、寿命及安全性等方面介绍了半导体照明产品检测实验室的建设方案,包括系统的功能、组成、基本的检测原理和方法等。     

Does the law of one price hold in a high-inflation environment? A tale of two cities in Turkey

This study addresses the price convergence in two cities in Turkey (Istanbul and Ankara) using annual data over the three-quarters of the twentieth century (1922–1998), characterized by prevailing high inflation rates for most of the period. In contrast to the rest of the literature addressing convergence in price levels with a typical result of extremely slow convergence rates at best, we argue that convergence is much easier detected in growth rates rather than levels of prices. We suggest using the bounds testing procedure of Pesaran et al. (2001) for this purpose. We find a clear-cut evidence on the existence of a common driving force behind inflation dynamics in Istanbul and Ankara – a finding that is in contrast with the results typically reported in related literature.     

Nonparametric fixed effects model for panel data with locally stationary regressors

We develop methods for inference in nonparametric time-varying fixed effects panel data models that allow for locally stationary regressors and for the time series length $T$ and cross-section size $N$ both being large. We first develop a pooled nonparametric profile least squares dummy variable approach to estimate the nonparametric function, and establish the optimal convergence rate and asymptotic normality of the resultant estimator. We then propose a test statistic to check whether the bivariate nonparametric function is time-varying or the time effect is separable, and derive the asymptotic distribution of the proposed test statistic. We present several simulated examples and two real data analyses to illustrate the finite sample performance of the proposed methods.     

经济增长与外商直接投资关系研究——基于上海市数据的实证分析

本文根据1990-2005年上海市GDP与FDI的时间序列数据分析,采用线性回归分析方法研究FDI与上海市经济增长之间的关系.格兰杰因果分析表明:上海市经济增长与外商直接投资之间存在着单向因果关系,即只存在从GDP到FDI的单向因果关系.之后的方差分析表明:上海市经济增长对于外商直接投资的影响非常显著,反之却影响甚微.而二者在长期中却有着因果关联性及互动关系.为此,在吸引外资战略上要采取长期而非短期的政策.