Multistage sampling for latent variable models

I consider the design of multistage sampling schemes for epidemiologic studies involving latent variable models, with surrogate measurements of the latent variables on a subset of subjects. Such models arise in various situations: when detailed exposure measurements are combined with variables that can be used to assign exposures to unmeasured subjects; when biomarkers are obtained to assess an unobserved pathophysiologic process; or when additional information is to be obtained on confounding or modifying variables. In such situations, it may be possible to stratify the subsample on data available for all subjects in the main study, such as outcomes, exposure predictors, or geographic locations. Three circumstances where analytic calculations of the optimal design are possible are considered: (i) when all variables are binary; (ii) when all are normally distributed; and (iii) when the latent variable and its measurement are normally distributed, but the outcome is binary. In each of these cases, it is often possible to considerably improve the cost efficiency of the design by appropriate selection of the sampling fractions. More complex situations arise when the data are spatially distributed: the spatial correlation can be exploited to improve exposure assignment for unmeasured locations using available measurements on neighboring locations; some approaches for informative selection of the measurement sample using location and/or exposure predictor data are considered.     

微分方程的解关于部分变元的弱吸引性

本文提出关于部分变元的弱吸引及其相关概念,并给出判定他们的充分条件。文献[]、[]中的相应结果可作为本文的特例。12     

集成电路中布尔线路图的优化设计

二叉决策图（BDDs)是布尔函数的一个表示方法,最近它被广泛应用于逻辑综合中布尔电路的模拟和测试等领域。在这些应用中,有些基本问题需要解决,其中包括电路图到决策图的转换。文章提出了一个转换的方法并分两步叙述,首先是对无扇出电路的转换,然后是对有扇出电路的转换,最后把两者结合为一个通用算法。     

半导体矩形量子阱中电光效应的探讨

通过密度矩阵及坐标变换等方法,导出质量可变的无限深矩阵阱中电光效应的解析表达械,通过对GaAs/AlAs量子阱的数值计算,指出电光效应的大小取决于因有效质量变化引起的阱不对称程度。     

谈变动成本法的应用

就变动成本法与财务成本核算实现合二为一核算体制———实行单轨核算,进行研究,提出一套行之有效的核算办法,这将有利于企业责任成本的落实和实施,减轻会计人员的工作量;有利于企业生产经营的短期预决策,提高应对市场的快速反映能力。     

带有潜变量的结构方程模型在突发事件应急管理中的应用

如何使事件与机构挂钩是突发事件应急管理中的一个重要问题;通过带有潜变量的结构方程模型能够建立起事件与机构之间的定量联系,从而为进一步对机构作评价和制定考核标准提供依据。     

基于非参数回归的遗漏变量检验

基于非参数回归提出了同时适用于横截面和时间序列数据的遗漏变量检验统计量.与现有文献相比,该统计量不仅避免了模型设定偏误问题,而且具有更高的局部检验功效,能够识别出速度更快的收敛到原假设的局部备择假设.该文选择单一带宽估计条件联合期望和条件边际期望,允许二者的非参数估计误差共同决定统计量的渐近分布,不仅改善了统计量的有限样本性质,而且避免了选择多个带宽和计算多个偏差项产生的繁杂工作.蒙特卡洛模拟结果表明该统计量具有良好的有限样本性质以及比Ait-Sahalia等更高的检验功效.实证分析采用该统计量捕获了F统计量无法识别的产出缺口与通胀之间关系,验证了非线性“产出一通胀”型菲利普斯曲线在中国的适用性.     

Estimation of population distribution function involving measurement error in the presence of non response

Abstract

This article addresses the problem of estimating population distribution function for simple random sampling in the presence of non response and measurement error together. We suggest a general class of estimators for estimating the cumulative distribution function using the auxiliary information. The expressions for the bias and mean squared error are derived up to the first order of approximation. The performance of the proposed class of estimators is compared with considered estimators both theoretically and numerically. A real data set is used to support the theoretical findings.     

社会保险成本过高是否抑制企业投资?

社会保险成本过高是否抑制企业投资，从而阻碍实体经济发展?对此，文章利用工业企业微观数据实证检验了企业社保成本变动对投资率的影响.为缓解内生性问题，文章选择城市老年人比重作为工具变量.实证检验显示企业社保支出比重增加1个单位标准差，企业投资率约下降3.3%，能够解释企业投资率变动的6.4%，具有较强经济显著性.文章还探究了社保成本变动影响企业投资的内在机制，发现劳动成本渠道、生产率渠道以及融资约束渠道都得到相关经验证据的支持.研究结果说明降低企业社保成本的政策如果能够得到有效落实，将会刺激企业扩大投资，促进地区经济发展.     

Improved methods for moment restriction models with data combination and an application to two-sample instrumental variable estimation

Combining-100 information from multiple samples is often needed in biomedical and economic studies, but differences between these samples must be appropriately taken into account in the analysis of the combined data. We study the estimation for moment restriction models with data combined from two samples under an ignorability-type assumption while allowing for different marginal distributions of variables common to both samples. Suppose that an outcome regression (OR) model and a propensity score (PS) model are specified. By leveraging semi-parametric efficiency theory, we derive an augmented inverse probability-weighted (AIPW) estimator that is locally efficient and doubly robust with respect to these models. Furthermore, we develop calibrated regression and likelihood estimators that are not only locally efficient and doubly robust but also intrinsically efficient in achieving smaller variances than the AIPW estimator when the PS model is correctly specified but the OR model may be mispecified. As an important application, we study the two-sample instrumental variable problem and derive the corresponding estimators while allowing for incompatible distributions of variables common to the two samples. Finally, we provide a simulation study and an econometric application on public housing projects to demonstrate the superior performance of our improved estimators. The Canadian Journal of Statistics 48: 259–284; 2020 © 2019 Statistical Society of Canada