Logistic regression and other discrete data models for serially correlated observations

Summary We consider the analysis of discrete serially correlated data in the presence of time dependent covariates. If the interest is to relate the covariates to the marginal distribution of the data, Markov chains are an obvious tool to consider, but their use is complicated by the fact that they are expressed in terms of transitional rather than marginal probabilities. We show how to parametrize the transition matrix in a suitable way so that interpretation is as desired. The focus is on binary and Poisson data, but the methodology can be adopted also with other discrete data distributions.     

信用本质的经济学分析

信用是经济主体之间达成契约、实现交易的必要条件,因此,信用不仅体现在延期交易和资金借贷这样的特殊交易形式中,也存在于一切形式的市场交易活动中。信用的本质就是对契约关系中的义务承担者履约意向、履约能力和履约后果的确定性预期。信用的运动表现为信用在时间和空间上的延续,信用的过度膨胀和过度收缩则是信用的两种畸形运动方式。一个经济主体和其他经济主体之间一旦形成外围中心式的信用结构,就会对社会经济生活产生重要影响。从局部信用和社会整体信用之间的关系看,局部信用的丧失通常会促使经济主体之间的契约趋于完备,但完备性契约能够降低风险、减少长期交易费用的假设是以良好的社会整体信用关系为前提的。因此,一个完善的制度环境是建设社会信用体系的坚实基础。     

基于前景价值与下偏二阶矩的投资组合优化研究

以均值方差模型为代表的现代投资组合理论基于经典期望效用理论,忽略了有限理性人决策行为特征及风险的心理感知对投资组合选择的影响。前景理论刻画了投资者行为特征并将其纳入到价值函数中,下偏矩方法对下侧风险的测度更符合人们对风险的心理感知,使两者在行为投资组合研究中得到广泛应用。基于前景价值与下偏二阶矩的投资组合模型兼顾投资者的价值与风险感知,在行为投资组合框架下,以区间数的方式将三参照点理论与前景理论参照效应结合,用基于前景价值的下偏二阶矩计量风险,建立投资组合优化模型,并利用有序加权平均算子求解。实证研究发现:基于前景价值和下偏二阶矩的投资组合模型与传统投资组合模型具有相似的有效前沿和更优的性质。基于前景价值与下偏二阶矩的投资组合模型拓展和丰富了投资组合理论。     

Transition psychology: the membership approach

改革开放以来的中国社会转型给中国社会心理学者提供了独特的社会实验室。为 了描述、理解和解释社会转型中的中国人心理和行为逻辑，应该呼唤直面社会转型的 社会心理学研究，或转型心理学的研究，以超越文化特异性路径和稳态社会路径。其 可能的核心构念是多元群体（成员）资格。

关键词: 转型心理学 文化特异性路径 稳态社会路径 部分群体资格

China's social transformation since reform and opening up in 1978 has provided a unique social laboratory for Chinese researchers of social psychology. In order to describe, understand and interpret the psychological and behavioral logic of the Chinese people, we need to call on social psychology research or social transition psychology research that looks directly at social transition, in order to go beyond the cultural exceptionalism and static society approaches. Multiple group membership is the potential core construct of such a psychology.     

On the distributions of the differences between the estimated autocorrelations and partial autocorrelations at the same lag

Pukkila (1982) introduced a new portmanteau-type test of white noise. The test is based on the differences between the estimated autocorrelations and the corresponding partial autocorrelations. In the present paper the distributions of these differences are consider in the case of normal white noise. Approximations to these distributions are given. Goodness of fit of these theoretical distributions and the corresponding observed distributions is studied using simulated time series of various lengths.     

A non-inferiority test for diagnostic accuracy in the absence of the golden standard test based on the paired partial areas under receiver operating characteristic curves

Non-inferiority tests are often measured for the diagnostic accuracy in medical research. The area under the receiver operating characteristic (ROC) curve is a familiar diagnostic measure for the overall diagnostic accuracy. Nevertheless, since it may not differentiate the diverse shapes of the ROC curves with different diagnostic significance, the partial area under the ROC (PAUROC) curve, another summary measure emerges for such diagnostic processes that require the false-positive rate to be in the clinically interested range. Traditionally, to estimate the PAUROC, the golden standard (GS) test on the true disease status is required. Nevertheless, the GS test may sometimes be infeasible. Besides, in a lot of research fields such as the epidemiology field, the true disease status of the patients may not be known or available. Under the normality assumption on diagnostic test results, based on the expectation-maximization algorithm in combination with the bootstrap method, we propose the heuristic method to construct a non-inferiority test for the difference in the paired PAUROCs without the GS test. Through the simulation study, although the proposed method might provide a liberal test, as a whole, the empirical size of the proposed method sufficiently controls the size at the significance level, and the empirical power of the proposed method in the absence of the GS is as good as that of the non-inferiority in the presence of the GS. The proposed method is illustrated with the published data.     

Estimation and Inference of Distributional Partial Effects: Theory and Application

This article considers nonparametric and semiparametric estimation and inference of the effects of a covariate, either discrete or continuous, on the conditional distribution of a response outcome. It also proposes various uniform tests following estimation. This type of analysis is useful in situations where the econometrician or policy-maker is interested in knowing the effect of a variable or policy on the whole distribution of the response outcome conditional on covariates and is not willing to make parametric functional form assumptions. Monte Carlo experiments show that the proposed estimators and tests are well-behaved in small samples. The empirical section studies the effect of minimum wage hikes on household labor earnings. It is found that the minimum wage has a heterogenous impact on household earnings in the U.S. and that small hikes in the minimum wage are more effective in improving the household earnings distribution.     

Failure time regression with continuous covariates measured with error

We consider failure time regression analysis with an auxiliary variable in the presence of a validation sample. We extend the nonparametric inference procedure of Zhou and Pepe to handle a continuous auxiliary or proxy covariate. We estimate the induced relative risk function with a kernel smoother and allow the selection probability of the validation set to depend on the observed covariates. We present some asymptotic properties for the kernel estimator and provide some simulation results. The method proposed is illustrated with a data set from an on-going epidemiologic study.     

由基函数选择辅助线性算子的方法

本文研究了同伦分析方法中由基函数选择有效的辅助线性算子的方法，并将其应用到同伦分析方法中，求解了一个非线性偏微分方程边值问题，并且获得了收敛的级数解．结果表明此方法是有效的，也有利于同伦分析方法的进一步研究．