Hierarchical Generalized Linear Models and Frailty Models with Bayesian Nonparametric Mixing

This paper proposes Bayesian nonparametric mixing for some well-known and popular models. The distribution of the observations is assumed to contain an unknown mixed effects term which includes a fixed effects term, a function of the observed covariates, and an additive or multiplicative random effects term. Typically these random effects are assumed to be independent of the observed covariates and independent and identically distributed from a distribution from some known parametric family. This assumption may be suspect if either there is interaction between observed covariates and unobserved covariates or the fixed effects predictor of observed covariates is misspecified. Another cause for concern might be simply that the covariates affect more than just the location of the mixed effects distribution. As a consequence the distribution of the random effects could be highly irregular in modality and skewness leaving parametric families unable to model the distribution adequately. This paper therefore proposes a Bayesian nonparametric prior for the random effects to capture possible deviances in modality and skewness and to explore the observed covariates' effect on the distribution of the mixed effects.     

AN ALGORITHMIC APPROACH TO BAYESIAN LINEAR MODEL CALCULATIONS

A framework is described for organizing and understanding the computations necessary to obtain the posterior mean of a vector of linear effects in a normal linear model, conditional on the parameters that determine covariance structure. The approach has two major uses; firstly, as a pedagogical tool in the derivation of formulae, and secondly, as a practical tool for developing computational strategies without needing complicated matrix formulae that are often unwieldy in complex hierarchical models. The proposed technique is based upon symbolic application of the sweep operator SWP to an appropriate tableau of means and covariances. The method is illustrated with standard linear model specifications, including the so-called mixed model, with both fixed and random effects.     

Estimating the Risks of Smoking, Air Pollution, and Passive Smoke on Acute Respiratory Conditions

Five years of the annual Health Interview Survey, conducted by the National Center for Health Statistics, are used to estimate the effects of air pollution, smoking, and environmental tobacco smoke on respiratory restrictions in activity for adults, and bed disability for children. After adjusting for several socioeconomic factors, the multiple regression estimates indicate that an independent and statistically significant association exists between these three forms of air pollution and respiratory morbidity. The comparative risks of these exposures are computed and the plausibility of the relative risks is examined by comparing the equivalent doses with actual measurements of exposure taken in the homes of smokers. The results indicate that: (1) smokers will have a 55-75% excess in days with respiratory conditions severe enough to cause reductions in normal activity; (2) a 1 microgram increase in fine particulate matter air pollution is associated with a 3% excess in acute respiratory disease; and (3) a pack-a-day smoker will increase respiratory restricted days for a nonsmoking spouse by 20% and increase the number of bed disability days for young children living in the household by 20%. The results also indicate that the estimates of the effects of secondhand smoking on children are improved when the mother's work status is known and incorporated into the exposure estimate.     

A new estimation procedure for a partially nonlinear model via a mixed‐effects approach

The authors consider the estimation of the parametric component of a partially nonlinear semiparametric regression model whose nonparametric component is viewed as a nuisance parameter. They show how estimation can proceed through a nonlinear mixed‐effects model approach. They prove that under certain regularity conditions, the proposed estimate is consistent and asymptotically Gaussian. They investigate its finite‐sample properties through simulations and illustrate its use with data on the relation between the photosynthetically active radiation and the net ecosystem‐atmosphere exchange of carbon dioxide.     

空间关系及其语言表达的认知语言学阐释

运用认知语言学中的空间参照框架理论和图形-背景关系理论探讨空间关系及其语言表达,具有十分重要的意义.空间关系是人对客观事物在空间中的方位、存现或运动状态的能动认知的结果.在空间关系所涉及的三要素中,目的物和参照物是基本的,是人观察和认识的基础,而人则是赋予事物以空间关系的关键.空间关系并不是存在于客观世界的自然之物,而是人类的能动识解使然.人们在识解事物之间的空间关系时,总是以一事物为参照来确定另一事物的空间方位.不同的识解方式和参照点形成了三类空间参照框架:相对参照框架,内在参照框架和绝对参照框架.人们在运用语言表达空间关系时,总是把目的物看做图形,把参照物看做背景,并以后者为参照来确定前者的空间位置.看做图形的目的物具有未知性和凸显性,看做背景的参照物具有已知性和确定性.     

从奢侈品消费看王尔德及其唯美主义

唯美主义和消费文化之间关系已得到广泛认同,唯美主义可以被进一步归类为消费社会中的奢侈品消费。王尔德及唯美主义对于纯粹形式美和艺术去道德化的关注与奢侈品消费的产生和发展有着密切的关系,但奢侈品消费者所追求的个我影响和人际影响在王尔德的文学创作中却形成了不可调和的矛盾,并最终导致了其个人和英国唯美主义的没落。     

Top management departures in cross-border acquisitions: Governance issues in an international context

This study examined top management team departures in U.S. manufacturing firms acquired by a foreign multinational during the six-year period following acquisition. Results indicated that greater cultural distance between the United States and the home country of the foreign multinational, higher levels of international integration in the target industry, and poor preacquisition performance in the U.S. target company were related to greater postacquisition top management departures. These effects were moderated significantly by the foreign acquirer’s international business and U.S. acquisition experience and showed different patterns over the short-term, intermediate-term, and long-term. Implications for future research on top management teams involved in cross-border acquisitions are discussed.     

语言与世界:对克里普克的后天必然真理的一个解释

传统观点认为先天真理一定是必然真理,后天真理一定是偶然真理,S.克里普克对此提出了挑战。他主张所有的名称的同一性陈述都是必然的,虽然它们常常只能凭经验才能被认识。对此我们可以给出如下解释:名称的同一性陈述并非关于世界是怎样的,它们的真假仅由我们的语言决定。但我们的语言并非与实际世界完全脱离,而是在实际世界中通过我们的活动建立的。这就是后天必然真理之所以可能。     

英语语言变异的视觉修辞效果论析

语言变异是偏离语言常规的一种语言形式,这种语言形式是对语言的创造性使用,往往有着特殊的修辞效果。本文着重探讨了英语语言变异中词汇变异和书写变异所产生的视觉修辞效果。