异质性大数据的分布式估计

随着物联网技术的进步,大数据给网络带宽和计算机存储能力带来巨大挑战,传统的集中式数据处理难以实现,客观上促进了分布式统计学习的发展。在无迭代算法研究中,Zhang等(2013)证明了当数据集个数s=O(N) 时,基于局部经验风险最小化的分治(DC)简单平均估计量具有O(N-1)均方误差收敛速度,Huang和Huo(2019)在M估计框架下进一步提出分布式一步估计量,但上述方法均未考虑海量数据可能存在的异质性对分治估计效果的影响。本文在线性模型框架下提出海量异质数据的分治一步加权估计,证明了估计量的渐近性质并考虑了异质性检验问题。将本文提出的方法应用于美国医疗保险实际数据分析,结果表明该方法能更好地拟合数据的线性趋势且显著提高了计算效率。     

Uniform Inference on Quantile Effects under Sharp Regression Discontinuity Designs

ABSTRACT

This study develops methods for conducting uniform inference on quantile treatment effects for sharp regression discontinuity designs. We develop a score test for the treatment significance hypothesis and Wald-type tests for the hypotheses related to treatment significance, homogeneity, and unambiguity. The bias from the nonparametric estimation is studied in detail. In particular, we show that under some conditions, the asymptotic distribution of the score test is unaffected by the bias, without under-smoothing. For situations where the conditions can be restrictive, we incorporate a bias correction into the Wald tests and account for the estimation uncertainty. We also provide a procedure for constructing uniform confidence bands for quantile treatment effects. As an empirical application, we use the proposed methods to study the effect of cash-on-hand on unemployment duration. The results reveal pronounced treatment heterogeneity and also emphasize the importance of considering the long-term unemployed.     

A monte carlo study of variable selection and inferences in a two stage random coefficient linear regression model with unbalanced data

A growth curve analysis is often applied to estimate patterns of changes in a given characteristic of different individuals. It is also used to find out if the variations in the growth rates among individuals are due to effects of certain covariates. In this paper, a random coefficient linear regression model, as a special case of the growth curve analysis, is generalized to accommodate the situation where the set of influential covariates is not known a priori. Two different approaches for seleaing influential covariates (a weighted stepwise selection procedure and a modified version of Rao and Wu’s selection criterion) for the random slope coefficient of a linear regression model with unbalanced data are proposed. Performances of these methods are evaluated by means of Monte-Carlo simulation. In addition, several methods (Maximum Likelihood, Restricted Maximum Likelihood, Pseudo Maximum Likelihood and Method of Moments) for estimating the parameters of the selected model are compared Proposed variable selection schemes and estimators are appliedtotheactualindustrial problem which motivated this investigation.     

Testing Heterogeneity for Frailty Distribution in Shared Frailty Model

Abstract

The frailties, representing extra variations due to unobserved measurements, are often assumed to be iid in shared frailty models. In medical applications, however, a speculation can arise that a data set might violate the iid assumption. In this paper we investigate this conjecture through an analysis of the kidney infection data in McGilchrist and Aisbett (McGilchrist, C. A., Aisbett, C. W. (1991). Regression with frailty in survival analysis. Biometrics 47:461–466). As a test procedure, we consider the cusum of squares test which is frequently used for monitoring a variance change in statistical models. Our result strongly sustains the heterogeneity of the frailty distribution.     

Omitted variables in longitudinal data models

The omission of important variables is a well‐known model specification issue in regression analysis and mixed linear models. The author considers longitudinal data models that are special cases of the mixed linear models; in particular, they are linear models of repeated observations on a subject. Models of omitted variables have origins in both the econometrics and biostatistics literatures. The author describes regression coefficient estimators that are robust to and that provide the basis for detecting the influence of certain types of omitted variables. New robust estimators and omitted variable tests are introduced and illustrated with a case study that investigates the determinants of tax liability.     

资源异质性、同质性与企业绩效关系研究--以我国医药类上市公司为例

不同企业之间的经营业绩持续地存在差异,但我们的研究表明,此差异将逐步地减小.资源的异质性假设很好地解释业绩差异的持续性,但难以解释为何此差异没有逐步增大.资源的可交易性、可分享性以及制度背景下对产品价值创造过程中标准化的要求致使企业的资源具有同质性,这一因素的存在导致了企业间赢利能力的差异化随时间而递减.     

对纵贯数据统计分析的认识

在介绍了纵贯数据的设计思想及优缺点基础上,从统计方法的角度讨论了纵贯数据在社会科学中所能发挥的作用。纵贯数据的优点在于其可以帮助我们进行对总体异质性的识别、对因果机制干预的研究、对因果效应的研究和对状态变换的研究。以一些基于纵贯数据的研究设计为实例,文章阐述了在研究中假设与数据紧密衔接的重要性,以及利用统计方法分析纵贯数据时需要考虑的要点。但由于存在着由人类和人类行为内在变异性导致的这一无法避免的根本性缺陷,纵贯数据并不能解决所有问题。因而在纵贯数据的辅助下,研究者需要对社会现象有更深入的理解,将其进行更合理的概念化,并加以更精准的数据分析。     

Tax morale and fairness in conflict an experiment

Most people pay their taxes most of the time, even if the expected disutility from enforcement is too low to deter tax evasion. One potential reason is tax morale and, more specifically, rule following. In a lab experiment, we show that the willingness to pay taxes just because participants are told they are supposed to pay is indeed pronounced. Yet compliance is reduced if participants learn that income is heterogeneous. The effect is driven by participants with the lowest income. The reduction obtains irrespective of the tax regime. If the tax is proportional to income, or progressive, participants become more skeptical about the willingness of participants with high income to comply.     

Altered resources, disturbance, and heterogeneity: A framework for comparing urban and non-urban soils

We propose a framework of key concepts useful in understanding how urban soils can contribute to general ecological theory. The major factors that can cause urban soils to be different from soils in non-urban ecosystems are identified and related to the familiar state factor approach. We evaluate directly altered resource availability, and the role of stress in mediating resource availability in urban ecosystems. Modified groundwater and stream flow, and atmospheric deposition of nitrogen and base cations are particularly important resource fluxes to soils in urban ecosystems. Disturbance can be conceptualized in the same way in urban as in non-urban ecosystems. However, in addition to biophysical disturbances familiar to ecologists studying wild lands, demographically and socially mediated changes in ecosystem structure must also be considered. These changes include human migration and population structure, institutional shifts, and the effects of human health. Finally, spatial heterogeneity, including fragmentation and differential connectivity, integrates the effects of resources and disturbance, and has an effect on subsequent resource availability and susceptibility to disturbance. Layers of heterogeneity include not only the geomorphic template, but urban climate, biotic composition, buildings and infrastructure, and demographic-social patterns. The complex layering of natural and social factors that constitute urban heterogeneity permit the continuation of important ecological processes, as well as modify ecological fluxes involving soils. We present a modification of the state factor approach as an expanded framework for the study of urban soils. The understanding of urban soils can contribute to general ecological theory by testing the generality of important ecosystem drivers and their linkage with social processes in an under investigated ecosystem type that is increasing in extent and impact worldwide.     

Parasitoid-mediated effects: apparent competition and the persistence of host–parasitoid assemblages

Indirect effects such as apparent competition (in which two hosts that do not compete for resources interact via a shared natural enemy) are increasingly being shown to be prevalent in the structure and function of ecological assemblages. Here, we review the empirical and theoretical evidence for these enemy-mediated effects in host–parasitoid assemblages. We first address questions about the design of experiments to test for apparent competition. Second, we consider factors likely to affect the coexistence of host species that share a parasitoid and are involved in apparent competition. We show that parasitoid aggregation, and the switching effect that this can generate when hosts occur in separate patches, not only promotes persistence but is also strongly stabilizing. The broader consequences of these effects are discussed. Received: November 6, 1998 / Accepted: January 13, 1999