ADDITIVE MODELS WITH PREDICTORS SUBJECT TO MEASUREMENT ERROR

This paper develops a likelihood‐based method for fitting additive models in the presence of measurement error. It formulates the additive model using the linear mixed model representation of penalized splines. In the presence of a structural measurement error model, the resulting likelihood involves intractable integrals, and a Monte Carlo expectation maximization strategy is developed for obtaining estimates. The method's performance is illustrated with a simulation study.     

Scientific Brain Drain and Human Capital Formation After the End of the Soviet Union

This article provides new empirical evidence on the impact of emigration on human capital formation by drawing upon the exodus of Russian scientists after the end of the Soviet Union. I create a novel panel data set based on scientific publications to identify former Soviet scientist émigrés and official Russian statistics on the production of PhDs aggregated at the regional and scientific field levels. I show that the emigration of scientists in the post‐Soviet period is associated with lower production of PhDs measured by admissions, graduates, and the number of students. The results suggest that emigration is not increasing investment in human capital at the PhD level. Possible explanations are that there is a lack of mentors to train the next generation of PhD students and that émigrés are acting as a channel for the younger generation to pursue PhD studies abroad.     

Accelerated test system strength models based on Birnbaum–Saunders distribution: a complete Bayesian analysis and comparison

Several models for studies related to tensile strength of materials are proposed in the literature where the size or length component has been taken to be an important factor for studying the specimens’ failure behaviour. An important model, developed on the basis of cumulative damage approach, is the three-parameter extension of the Birnbaum–Saunders fatigue model that incorporates size of the specimen as an additional variable. This model is a strong competitor of the commonly used Weibull model and stands better than the traditional models, which do not incorporate the size effect. The paper considers two such cumulative damage models, checks their compatibility with a real dataset, compares them with some of the recent toolkits, and finally recommends a model, which appears an appropriate one. Throughout the study is Bayesian based on Markov chain Monte Carlo simulation.     

Feature significance in generalized additive models

This paper develops inference for the significance of features such as peaks and valleys observed in additive modeling through an extension of the SiZer-type methodology of Chaudhuri and Marron (1999) and Godtliebsen et al. (2002, 2004) to the case where the outcome is discrete. We consider the problem of determining the significance of features such as peaks or valleys in observed covariate effects both for the case of additive modeling where the main predictor of interest is univariate as well as the problem of studying the significance of features such as peaks, inclines, ridges and valleys when the main predictor of interest is geographical location. We work with low rank radial spline smoothers to allow to the handling of sparse designs and large sample sizes. Reducing the problem to a Generalised Linear Mixed Model (GLMM) framework enables derivation of simulation-based critical value approximations and guards against the problem of multiple inferences over a range of predictor values. Such a reduction also allows for easy adjustment for confounders including those which have an unknown or complex effect on the outcome. A simulation study indicates that our method has satisfactory power. Finally, we illustrate our methodology on several data sets.     

A Bayes comparison of Weibull extension and modified Weibull models for data showing bathtub hazard rate

A number of models have been proposed in the literature to model data reflecting bathtub-shaped hazard rate functions. Mixture distributions provide the obvious choice for modelling such data sets but these contain too many parameters and hamper the accuracy of the inferential procedures particularly when the data are meagre. Recently, a few distributions have been proposed which are simply generalizations of the two-parameter Weibull model and are capable of producing bathtub behaviour of the hazard rate function. The Weibull extension and the modified Weibull models are two such families. This study focuses on comparing these two distributions for data sets exhibiting bathtub shape of the hazard rate. Bayesian tools are preferred due to their wide range of applicability in various nested and non-nested model comparison problems. Real data illustrations are provided so that a particular model can be recommended based on various tools of model comparison discussed in the paper.     

COMPLEMENTARITIES,MULTIPLICITY, AND SUPPLY INFORMATION

If traders can obtain private information about the payoff and the supply of a stock then there can exist (i) complementarity in information acquisition and (ii) multiple equilibria in the financial and information markets. The additional dimension of supply information increases coordination possibilities in the financial market, leading to multiple equilibria. The existence of two information sources can lead to information acquisition being complementary. The multiplicity of equilibria is suggestive of excess volatility and crashes. The different financial market equilibria imply differing patterns of cost of capital and volume of trade. (JEL: D82, D83, G14)     

Gambling Participation and Social Support Among Older Adults: A Longitudinal Community Study

The purpose of this preliminary study was to examine associations between leaving home to engage in bingo or gambling activity and indices of physical and mental health and social support among a representative community cohort of 1016 elderly people. Cross-sectional and longitudinal data gathered from a prospective epidemiological study in a rural, low socio-economic status, area of Pennsylvania was employed. The cohort had a mean age of 78.8 (SD = 5.1) (range 71–97) and participated in three consecutive biennial waves of data collection. Nearly half (47.7) of the cohort reported gambling. To predict gambling, the independent variables included age, sex, education, employment, social support, depressive symptoms, self-rated health, alcohol use, cigarette use, and cognitive functioning. In cross-sectional, univariate analyses, gambling was associated with younger age, sex (male), fewer years of education, greater social support, lower depression scores, better self-rated health, alcohol use in the past year, and higher cognitive functioning. In a cross-sectional multiple regression model, younger age, greater social support, and alcohol use in the past year remain strongly and independently associated with gambling activity. Longitudinally, age, sex, social support, alcohol use, and gambling are predictive of future gambling activity. The results revealed that gambling may offer a forum of social support to older adults who are often isolated as they age.     

Determination of the functional form of the relationship of covariates to the log hazard ratio in a Cox model

In this paper, we review available methods for determination of the functional form of the relation between a covariate and the log hazard ratio for a Cox model. We pay special attention to the detection of influential observations to the extent that they influence the estimated functional form of the relation between a covariate and the log hazard ratio. Our paper is motivated by a data set from a cohort study of lung cancer and silica exposure, where the nonlinear shape of the estimated log hazard ratio for silica exposure plotted against cumulative exposure and hereafter referred to as the exposure–response curve was greatly affected by whether or not two individuals with the highest exposures were included in the analysis. Formal influence diagnostics did not identify these two individuals but did identify the three highest exposed cases. Removal of these three cases resulted in a biologically plausible exposure–response curve.