Bayesian analysis of outlier problems using divergence measures

A Bayesian approach is presented for detecting influential observations using general divergence measures on the posterior distributions. A sampling-based approach using a Gibbs or Metropolis-within-Gibbs method is used to compute the posterior divergence measures. Four specific measures are proposed, which convey the effects of a single observation or covariate on the posterior. The technique is applied to a generalized linear model with binary response data, an overdispersed model and a nonlinear model. An asymptotic approximation using Laplace method to obtain the posterior divergence is also briefly discussed.     

关于有效促进社会公正的几个问题

本文认为:(1)为了顺利地推进改革,为了中国社会经济持续、有效和健康的发展,就必须适应新的历史条件,顺应民意、顺应现代社会的基本趋势,把社会公正放到一个突出的位置。(2)在中国现阶段应当开始建立一个初级的社会公平保障体系。初级社会公平保障体系的基本特征是低水准、广覆盖、有实效。对于国家来说,近期需要做的事情可以分为两大块,一是国家的直接投入,二是国家的立法、监督、执行和引导。(3)有一些根深蒂固的观念在妨碍着我们重视社会公正问题。这些观念主要包括:“原始积累不可避免”,“国家财力不足”,“重视公正便会妨碍效率”,因此我们必须对这些观念进行一番必要的反思。(4)要想构建一个公正而和谐的社会,就必须培育一个庞大的中等收入者人群,形成一个“两头小,中间大”的橄榄型的社会结构,那么社会就会变得越来越稳定了。     

Two point priors and Γ-minimax estimating in families of uniform distributions

It is shown that when a parameter lying in a sufficiently small interval is to be estimated in a family of uniform distributions, a two point prior is least favourable under squared error loss. The unique Bayes estimator with respect to this prior is minimax. The Γ-minimax estimator is derived for sets Γ of priors consisting of all priors that give fixed probabilities to two specified subintervals of the parameter space if a two point prior is least favourable in Γ.     

20世纪美国黑人大迁徙与南部三农问题之关系

南北战争后,美国南部长期面临农业生产方式落后、农民贫困、农村社会发展缓慢等三农问题。上述问题与南部的种族问题相互交织,加剧了南部社会的落后与黑暗。这其中,南部黑人受害最为深重,他们被迫大规模迁徙到美国其他地区。20世纪美国有两次黑人大迁徙的高潮,到20世纪70年代有600多万南部黑人迁徙。美国南部的三农问题是黑人大迁徙的经济原因,但黑人大迁徙又反过来推动了三农问题的解决,由此可见迁徙自由对于解决三农问题的重要意义。     

A probablistic analysis for an optimal screening problem

Summary We consider a lotL formed byN apparently similar unitsW ₁,…,W _N, where each of theW _i may come from one of two different populationsP ₁ andP ₂;T ₁,…,T _N denote the corresponding lifetimes. The units fromP _i undergo a failure of kindi and their survival function isS _i (t). We assume that the failure rate function are known and that the units fromP ₁ are ?substandard?: λ ₁ (t)≥λ ₂ (t), ∀t≥0. We want to putW ₁,…,W _N under a pre-operational test (burn-in test) in order to eliminate at least a great part of the substandard units and we face the problem of obtaining a rule for stopping the test under the assumption that, with the failure of a unit, it is possible to recognize the population from which the unit comes. Such a problem will be formalized as an optimal stopping problem for a suitably defined Markov process. Our study shall evidentiate some fundamental aspects of the problem and the role of the prior distribution of the (random) numberM ₀ of those units inL coming fromP ₁ (substandard). The latter distribution has a great influence on the form of the solution. This research was supported by the C.N.R. Project ?Statistica Bayesiana e Simulazione in Affidalità e Modellistica Biologica?.     

Evaluating a private foundation's health program

Public policy decisions in health are increasingly difficult and expensive. Although there will never be enough information available, private foundations can help to bridge the most important gaps in knowledge. Larger foundations may also wish to respond to those who doubt the value of foundation activities. This article reviews the experiences over the past eight years of The Robert Wood Johnson Foundation in employing evaluation and related social research procedures in the planning and implementation of a major philanthropic effort to improve the health and medical care of Americans. Discussed are the still evolving Foundation evaluation framework, the unanticipated problems in undertaking specific evaluations, and the substantive findings of some of the studies.     

Using In Vitro High‐Throughput Screening Data for Predicting Benzo[k]Fluoranthene Human Health Hazards

Today there are more than 80,000 chemicals in commerce and the environment. The potential human health risks are unknown for the vast majority of these chemicals as they lack human health risk assessments, toxicity reference values, and risk screening values. We aim to use computational toxicology and quantitative high‐throughput screening (qHTS) technologies to fill these data gaps, and begin to prioritize these chemicals for additional assessment. In this pilot, we demonstrate how we were able to identify that benzo[k]fluoranthene may induce DNA damage and steatosis using qHTS data and two separate adverse outcome pathways (AOPs). We also demonstrate how bootstrap natural spline‐based meta‐regression can be used to integrate data across multiple assay replicates to generate a concentration–response curve. We used this analysis to calculate an in vitro point of departure of 0.751 μM and risk‐specific in vitro concentrations of 0.29 μM and 0.28 μM for 1:1,000 and 1:10,000 risk, respectively, for DNA damage. Based on the available evidence, and considering that only a single HSD17B4 assay is available, we have low overall confidence in the steatosis hazard identification. This case study suggests that coupling qHTS assays with AOPs and ontologies will facilitate hazard identification. Combining this with quantitative evidence integration methods, such as bootstrap meta‐regression, may allow risk assessors to identify points of departure and risk‐specific internal/in vitro concentrations. These results are sufficient to prioritize the chemicals; however, in the longer term we will need to estimate external doses for risk screening purposes, such as through margin of exposure methods.     

A modified LGB method for detecting significant effects based on a half-normal probability plot

In analyzing data from unreplicated factorial designs, the half-normal probability plot is commonly used to screen for the ‘vital few’ effects. Recently, many formal methods have been proposed to overcome the subjectivity of this plot. Lawson (1998) (hereafter denoted as LGB) suggested a hybrid method based on the half-normal probability plot, which is a blend of Lenth (1989) and Loh (1992) method. The method consists of fitting a simple least squares line to the inliers, which are determined by the Lenth method. The effects exceeding the prediction limits based on the fitted line are candidates for the vital few effects. To improve the accuracy of partitioning the effects into inliers and outliers, we propose a modified LGB method (hereafter denoted as the Mod_LGB method), in which more outliers can be classified by using both the Carling’s modification of the box plot (Carling, 2000) and Lenth method. If no outlier exists or there is a wide range in the inliers as determined by the Lenth method, more outliers can be found by the Carling method. A simulation study is conducted in unreplicated $2^4$ designs with the number of active effects ranging from 1 to 6 to compare the efficiency of the Lenth method, original LGB methods, and the proposed modified version of the LGB method.     

Majority size and conformity behavior in charitable giving: Field evidence from a donation-based crowdfunding platform in Japan

A charitable donor typically imitates the majority contribution of other donors. This study examines the relationships between majority size and this so-called donor’s conformity behavior, by empirically investigating the impacts of multiple earlier donations on the donation of a subsequent donor to JapanGiving, a donation-based crowdfunding platform in Japan. This analysis is possible because the platform’s webpage displays the previous donation amounts in chronological order, thus allowing us to examine the modal amount of more recent donations. By using data on 9989 actual donations, our dynamic panel analysis suggests that when the number of most recent continuous modal donations increases, the likelihood that a subsequent donor matches the modal amount increases. This result supports the notion that a donor’s conformity behavior is more likely to occur when a greater proportion of other donors give a similar amount. Furthermore, the effects of continuous modal donations are strongly observed for low monetary ranges. We interpret that initiating further cooperation among a large number of less cooperative other donors would become harder, or individuals would obtain an excuse for less cooperation due to the others’ behaviors. Finally, we discuss how our findings connect economic studies of charity and social psychology studies of conformity and could help improve the effectiveness of fundraising by charities.