多属性逆向拍卖中信息披露负效应的成因与应对策略

信息披露正在被越来越多地应用于拍卖过程,主要起调节报价的作用。然而,信息披露在多属性逆向拍卖中潜在的负效应也逐渐展露,主要表现为供应商利润下降、拍卖无效、商业机密泄露等。究其成因,主要有信息的敏感性、披露的复杂性和供应商感知的差异性。因此,针对以上现象及其成因采用供应商合谋、逆向选择、提高竞争力等应对策略,将有助于完善逆向拍卖机制。     

Bayesian approach to estimation of intraclass correlation using reference prior

For the balanced variance component model when the intraclass correlation coefficient is of interest, Bayesian analysis is often appropriate. Berger and Bernardo’s (1992a) grouped ordering reference prior approach is used to analyze this model. The reference priors are developed and compared for the posterior inference with real and simulated data. We examine whether the reference priors satisfy the probability-matching criterion. Further, the reference prior is shown to be good in the sense of correct frequentist coverage probability of the posterior quantile.     

语言哲学传统与形而上学指称观念——答江怡教授的质疑

在语言哲学中,占有统治地位的指称观念与纯粹语义学的指称观念是对立的。所谓的传统指称观念,也可以称之为形而上学指称观念,其核心是认定指称性语言表达意指语言外世界中的对象。江怡教授认为《语言.意义.指称——自主的意义与实在》一书误读了语言哲学传统,那是因为传统的指称观念并不是书中所说的形而上学指称观念,而多少接近于纯粹语义学指称观念。但是,实际上分析哲学传统的主流倾向是肯定形而上学指称观念的,这个观念过去一直主导着语言与世界关系的讨论。     

Multilevel regression mixture analysis

Summary.  A two-level regression mixture model is discussed and contrasted with the conventional two-level regression model. Simulated and real data shed light on the modelling alternatives. The real data analyses investigate gender differences in mathematics achievement from the US National Education Longitudinal Survey. The two-level regression mixture analyses show that unobserved heterogeneity should not be presupposed to exist only at level 2 at the expense of level 1. Both the simulated and the real data analyses show that level 1 heterogeneity in the form of latent classes can be mistaken for level 2 heterogeneity in the form of the random effects that are used in conventional two-level regression analysis. Because of this, mixture models have an important role to play in multilevel regression analyses. Mixture models allow heterogeneity to be investigated more fully, more correctly attributing different portions of the heterogeneity to the different levels.     

Reference priors for a product of normal means when variances are unknown

The reference priors of Berger and Bernardo (1992) are derived for normal populations with unknown variances when the product of means is of interest. The priors are also shown to be Tibshirani's (1989) matching priors.     

Likelihood Inference for Unions of Interacting Discs

Abstract. This is probably the first paper which discusses likelihood inference for a random set using a germ‐grain model, where the individual grains are unobservable, edge effects occur and other complications appear. We consider the case where the grains form a disc process modelled by a marked point process, where the germs are the centres and the marks are the associated radii of the discs. We propose to use a recent parametric class of interacting disc process models, where the minimal sufficient statistic depends on various geometric properties of the random set, and the density is specified with respect to a given marked Poisson model (i.e. a Boolean model). We show how edge effects and other complications can be handled by considering a certain conditional likelihood. Our methodology is illustrated by analysing Peter Diggle's heather data set, where we discuss the results of simulation‐based maximum likelihood inference and the effect of specifying different reference Poisson models.     

Modeling longitudinal count data with dropouts

This paper explores the utility of different approaches for modeling longitudinal count data with dropouts arising from a clinical study for the treatment of actinic keratosis lesions on the face and balding scalp. A feature of these data is that as the disease for subjects on the active arm improves their data show larger dispersion compared with those on the vehicle, exhibiting an over‐dispersion relative to the Poisson distribution. After fitting the marginal (or population averaged) model using the generalized estimating equation (GEE), we note that inferences from such a model might be biased as dropouts are treatment related. Then, we consider using a weighted GEE (WGEE) where each subject's contribution to the analysis is weighted inversely by the subject's probability of dropout. Based on the model findings, we argue that the WGEE might not address the concerns about the impact of dropouts on the efficacy findings when dropouts are treatment related. As an alternative, we consider likelihood‐based inference where random effects are added to the model to allow for heterogeneity across subjects. Finally, we consider a transition model where, unlike the previous approaches that model the log‐link function of the mean response, we model the subject's actual lesion counts. This model is an extension of the Poisson autoregressive model of order 1, where the autoregressive parameter is taken to be a function of treatment as well as other covariates to induce different dispersions and correlations for the two treatment arms. We conclude with a discussion about model selection. Published in 2009 by John Wiley & Sons, Ltd.     

Reference Groups,Mob Mentality,and Bystander Intervention: A Sociological Analysis of the Lara Logan Case1

Despite that it involves mobs, bystanders, and political theater—three classic concepts in social psychology—academics have neglected analyzing the Lara Logan sexual assault case through these lenses. I explore how the case has been discussed in the media and suggest that analysis of the mob and bystanders has been, oddly, lacking. I argue that the best reference group to use when discussing this case is not other journalists or even other women who have survived assaults, but is instead enemy women who have survived politically motivated wartime gang sexual assaults. Most observers have overlooked the relevant reference group due to focusing on the traits of the victim, rather than on the context of the event itself. I argue that the case conforms to important dimensions: (1) the sociological norm that gang violence involves premeditation, (2) an agreement of values among perpetrators, and (3) that the violence itself lacked cultural and social legitimacy. Logan was likely targeted because she was a “stranger”; she was saved, in part, for the same reason. The case illustrates known patterns of mob mentalities and bystander intervention, yet it is unlike most cases of both nonwartime gender violence and violence against journalists.     

Income Comparison as a Determining Mechanism of Class Identification: A Quantitative and Simulation Study Using Japanese Survey Data

This paper questions whether personal income comparison explains the distributive gap between income and class identification by exploring the following two issues: empirical validity of income comparison as the determinant of class identification, and theoretical validity of income comparison for the distributive gap. For the first issue, we conduct a statistical analysis using data from the Social Stratification and Social Mobility surveys (1975–2005), and the Stratification and Social Psychology-I survey (2010). We find that the criteria for choosing reference groups changed historically from residential proximity to occupational equality. In addition, income comparison with sensitive to lower-income possessors and a distorted perception of income difference significantly affected class identification, except for the year of 1985. The simulation analysis employed to examine the second issue clarified that income comparison with the above-mentioned features yields a less skewed distribution compared to that of class identification. The data also indicates that the empirical conditions of income are satisfied for realization of this result. Thus, we could ascertain empirical and theoretical validity of income comparison as explanation for the distributive gap between income and class identification.