Estimation and influence diagnostics for zero-inflated hyper-Poisson regression model: full Bayesian analysis

The purpose of this paper is to develop a Bayesian analysis for the zero-inflated hyper-Poisson model. Markov chain Monte Carlo methods are used to develop a Bayesian procedure for the model and the Bayes estimators are compared by simulation with the maximum-likelihood estimators. Regression modeling and model selection are also discussed and case deletion influence diagnostics are developed for the joint posterior distribution based on the functional Bregman divergence, which includes ψ-divergence and several others, divergence measures, such as the Itakura–Saito, Kullback–Leibler, and χ² divergence measures. Performance of our approach is illustrated in artificial, real apple cultivation experiment data, related to apple cultivation.     

Semiparametric Proportional Odds Models for Spatially Correlated Survival Data

The last decade has witnessed major developments in Geographical Information Systems (GIS) technology resulting in the need for statisticians to develop models that account for spatial clustering and variation. In public health settings, epidemiologists and health-care professionals are interested in discerning spatial patterns in survival data that might exist among the counties. This paper develops a Bayesian hierarchical model for capturing spatial heterogeneity within the framework of proportional odds. This is deemed more appropriate when a substantial percentage of subjects enjoy prolonged survival. We discuss the implementation issues of our models, perform comparisons among competing models and illustrate with data from the SEER (Surveillance Epidemiology and End Results) database of the National Cancer Institute, paying particular attention to the underlying spatial story.     

Robustness of some designs against missing data

This article studies the robustness of several types of designs against missing data. The robustness of orthogonal resolution III fractional factorial designs and second-order rotatable designs is studied when a single observation is missing. We also study the robustness of balanced incomplete block designs when a block is missing and of Youden square designs when a column is missing.     

Selection of regressors in econometrics: parametric and nonparametric methods selection of regressors in econometrics

The present paper addresses the selection-of-regressors issue into a general discrimination framework. We show how this framework is useful in unifying various procedures for selecting regressors and helpful in understanding the different strategies underlying these procedures. We review selection of regressors in linear, nonlinear and nonparametric regression models. In each case we successively consider model selection criteria and hypothesis testing procedures.     

Directors’ human capital,firm strategy,and firm performance

Ideally, corporations are directed by boards whose directors provide valuable human capital that match the firms’ strategy. We investigate how directors’ human capital (international experience, industrial know-how, CEO experience, and financial know-how) affects firm performance including the firm’s strategy (diversification and internationalization) and how human capital is related to acquisition strategies (non-diversifying and international acquisitions). Our sample consists of 560 firm-year observations in Switzerland. We find empirical evidence that directors’ human capital affects firm performance and that this relationship depends on the firm’s strategy. Furthermore, human capital is also correlated with acquisition strategy. The study shows that focusing on board independence and compliance issues may be unrewarding in board research and practice.     

Bayesian analysis of generalized odds-rate hazards models for survival data

In the analysis of censored survival data Cox proportional hazards model (1972) is extremely popular among the practitioners. However, in many real-life situations the proportionality of the hazard ratios does not seem to be an appropriate assumption. To overcome such a problem, we consider a class of nonproportional hazards models known as generalized odds-rate class of regression models. The class is general enough to include several commonly used models, such as proportional hazards model, proportional odds model, and accelerated life time model. The theoretical and computational properties of these models have been re-examined. The propriety of the posterior has been established under some mild conditions. A simulation study is conducted and a detailed analysis of the data from a prostate cancer study is presented to further illustrate the proposed methodology.     

Ad-Hoc Reviewers from 2009

Acknowledgments

Ad-Hoc Reviewers from 2009     

Level of self-reported neck/shoulder pain and biomechanical workload in cleaners

The aim of the present study was to investigate the relation between self-reported pain, muscular activity and postural load during cleaning tasks. Eighteen cleaners performed usual cleaning tasks in both a laboratory and a lecture room. The level of perceived pain in the neck-shoulder region during the last 7 days was recorded. Bipolar surface electromyography (SEMG) was recorded bilaterally from upper trapezius and erector spinae muscles during cleaning. Root mean square (RMS) and permutation entropy (PE) values representing amplitude and complexity of SEMG time-series were estimated. A tri-axial accelerometer package was mounted on the low back (L5-S1) to measure postural changes during cleaning tasks. The 10th, 50th and 90th percentiles of the angular distributions were computed to characterize postures and movements. Pain tended to play a significant role on RMS of left/right trapezius and left erector spinae muscles (P≤0.08). Cleaners with low pain level exhibited higher muscular activity during cleaning. Pain played or tended to play a significant role on PE of left and right erector spinae muscles (P≤0.08). Pain played a significant role on the 10th, 50th and 90th percentile (P<0.05) of lateral flexion angle (side bending). The present study emphasizes biomechanical adaptations occurring in presence of neck-shoulder pain during cleaning tasks.     

Coordination and artifacts in joint activity: the case of tagging in high-risk industries

The social, organizational, and technological complexity of high-risk organizations creates a strong need for coordination. Joint activity in such systems thus relies both on formal coordination and on a set of informal coordinative practices. Coordinated joint activity is documented in this paper from two perspectives: the development of coordinative practices to overcome the limitations of formal coordination, and the use of artifacts for coordinative purposes. The empirical material is provided by a workplace study undertaken according to theoretical conceptions of situated action and cognition. It was undertaken in the context of a design project that aims at improving the tagout process in a high-risk industry. Findings first describe and analyze situations in which formal coordination turned out to be more of a constraint than a resource for effective action. They then illustrate the role played by artifacts in coordinated activity, focusing on the use of a particular artifact, the tagout tag, in different situations.     

Robust linear mixed models with skew-normal independent distributions from a Bayesian perspective

Linear mixed models were developed to handle clustered data and have been a topic of increasing interest in statistics for the past 50 years. Generally, the normality (or symmetry) of the random effects is a common assumption in linear mixed models but it may, sometimes, be unrealistic, obscuring important features of among-subjects variation. In this article, we utilize skew-normal/independent distributions as a tool for robust modeling of linear mixed models under a Bayesian paradigm. The skew-normal/independent distributions is an attractive class of asymmetric heavy-tailed distributions that includes the skew-normal distribution, skew-t, skew-slash and the skew-contaminated normal distributions as special cases, providing an appealing robust alternative to the routine use of symmetric distributions in this type of models. The methods developed are illustrated using a real data set from Framingham cholesterol study.