A Bayesian Adjustment for Covariate Misclassification with Correlated Binary Outcome Data

Estimated associations between an outcome variable and misclassified covariates tend to be biased when the methods of estimation that ignore the classification error are applied. Available methods to account for misclassification often require the use of a validation sample (i.e. a gold standard). In practice, however, such a gold standard may be unavailable or impractical. We propose a Bayesian approach to adjust for misclassification in a binary covariate in the random effect logistic model when a gold standard is not available. This Markov Chain Monte Carlo (MCMC) approach uses two imperfect measures of a dichotomous exposure under the assumptions of conditional independence and non-differential misclassification. A simulated numerical example and a real clinical example are given to illustrate the proposed approach. Our results suggest that the estimated log odds of inpatient care and the corresponding standard deviation are much larger in our proposed method compared with the models ignoring misclassification. Ignoring misclassification produces downwardly biased estimates and underestimate uncertainty.     

Generations,Identities, and the Collective Memory of Che Guevara1

Has the image of Che Guevara lost its power to evoke radical politics in the face of pervasive commodification? The commercialization of this 1960s political icon has called into question the power of the market to shape collective memories. Meanwhile, antisystemic movements of the left continue to erect his image at protest events. In light of this contest over how Che Guevara is remembered, we investigate, using data from a survey of Spanish citizens, who is most likely to recall him. We find qualified support for the theory of generational imprinting—Che is more often recalled by those generations who saw him rise to prominence during their formative years, although prominent as a collective symbol rather than as a living person. Our results also corroborate the claim that historical figures or events are more salient for, and therefore more likely to be remembered by, some subgenerational units than others. Thus, although the younger generations are in general more likely than their elders to recall Che, he is most frequently remembered by the highly educated leftists who espouse postmaterialist and posttraditionalist values and identify more with their local regions than with the nation of Spain. These patterns suggest that, in contrast to the dire predictions of mass culture theorists, the memory of Che Guevara has become increasingly tied to markers of social, ethnic‐regional, and political identity.     

如何成为"最佳雇主"--访翰威特咨询公司

随着社会发展，越来越多的企业意识到“人才”是企业最宝贵的无形资产，吸引和留用具有一技之长的员工已经成为一个棘手的问题。为此，著名的全球HR管理咨询公司———翰威特咨询公司在２００１年推出了“亚洲最佳雇主”调研活动，２００２年他们再次进行了评选活动。争当“最佳雇主”成为企业竞争的一个大方向。如何才能成为“最佳雇主”？这个评选是怎么进行的？评选活动对现实有什么意义？带着这些问题，记者采访了翰威特公司北京地区负责人林靖小姐及其资询顾问。记：据了解，翰威特２００１年在中国开展“最佳雇主”的调研还是第一次…     

Privatization of refuse removal and labor costs

We examine the labor-cost savings associated with privatization by comparing earnings and employment trends of public and private sector refuse workers. Findings suggest that high union earnings for workers in the public sector are a source of labor-cost savings in the refuse industry. Evidence on job changers does not indicate that earnings for this group of workers are a compensating differential. Metropolitan area employment findings suggest that municipalities are less likely to use union refuse workers in the public sector when a relatively small percentage of area residents belong to a union. The authors thank Jacqueline Agesa, Keith Bender, Maria Crawford, and Richard Perlman for valuable suggestions. Research assistance from Eric Blackburn is greatly appreciated.     

Diagnostics for dependence within time series extremes

Summary. The analysis of extreme values within a stationary time series entails various assumptions concerning its long- and short-range dependence. We present a range of new diagnostic tools for assessing whether these assumptions are appropriate and for identifying structure within extreme events. These tools are based on tail characteristics of joint survivor functions but can be implemented by using existing estimation methods for extremes of univariate independent and identically distributed variables. Our diagnostic aids are illustrated through theoretical examples, simulation studies and by application to rainfall and exchange rate data. On the basis of these diagnostics we can explain characteristics that are found in the observed extreme events of these series and also gain insight into the properties of events that are more extreme than those observed.     

Tomb, temple, machine and self: the social construction of the body.

The body is socially constructed; and in this paper we explore the various and ever-changing constructions of the body, and thus of the embodied self, from the Greeks to the present. The one word, body, may therefore signify very different realities and perceptions of reality; and we consider briefly how and why these meanings changed. Plato believed the body was a 'tomb', Paul said it was the 'temple' of the Holy Spirit, the Stoic philosopher Epictetus taught that it was a 'corpse'. Christians believed, and believe, that the body is not only physical, but also spiritual and mystical, and many believed it was an allegory of church, state and family. Some said it was cosmic: one with the planets and the constellations. Descartes wrote that the body is a 'machine', and this definition has underpinned biomedicine to this day; but Sartre said that the body is the self. In sum, the body has no intrinsic meaning. Populations create their own meanings, and thus their own bodies; but how they create, and then change them, and why, reflects the social body.     

BURR CRITICAL VALUE APPROXIMATIONS FOR TESTS OF AUTOCORRELATION AND HETEROSCEDASTICITY

The paper evaluates the accuracy of Burr approximations of critical values and p-values for test a of autocorrelation and heteroscedasticity in the linear regression model.