Influence Diagnostics for a Skew Extension of the Grubbs Measurement Error Model

Influence diagnostics methods are extended in this article to the Grubbs model when the unknown quantity x (latent variable) follows a skew-normal distribution. Diagnostic measures are derived from the case-deletion approach and the local influence approach under several perturbation schemes. The observed information matrix to the postulated model and Delta matrices to the corresponding perturbed models are derived. Results obtained for one real data set are reported, illustrating the usefulness of the proposed methodology.

A robust Bayesian approach to null intercept measurement error model with application to dental data

Measurement error models often arise in epidemiological and clinical research. Usually, in this set up it is assumed that the latent variable has a normal distribution. However, the normality assumption may not be always correct. Skew-normal/independent distribution is a class of asymmetric thick-tailed distributions which includes the Skew-normal distribution as a special case. In this paper, we explore the use of skew-normal/independent distribution as a robust alternative to null intercept measurement error model under a Bayesian paradigm. We assume that the random errors and the unobserved value of the covariate (latent variable) follows jointly a skew-normal/independent distribution, providing an appealing robust alternative to the routine use of symmetric normal distribution in this type of model. Specific distributions examined include univariate and multivariate versions of the skew-normal distribution, the skew-t distributions, the skew-slash distributions and the skew contaminated normal distributions. The methods developed is illustrated using a real data set from a dental clinical trial. (C) 2008 Elsevier B.V. All rights reserved.

Assessing Threshold Concepts for Information Literacy

This presentation was offered as part of the CUNY Library Assessment Conference, Reinventing Libraries: Reinventing Assessment, held at the City University of New York in June 2014.

Beyond the Threshold: Life in the New Russia

Amanda Sprang spent nine months, from September of 1995 to May of 1996, studying at Colby College's program in St. Petersburg, Russia. Through contacts made during previous trips to Russia in middle and high school, Amanda was able to quickly rekindle her old friendships and make new ones with many young Russians from different backgrounds. The following work is a collection of twelve essays about life in the New Russia. The essays are framed by a foreword and an epilogue that help place the entire work in a historical context. Although the theme of each essay emerges from a particular incident, within every story Amanda has addressed numerous topics relating to Russian life in today’s changing society. Her first essay, “Art Klinika," takes place in an avant-garde night club in St. Petersburg, and includes a brief yet impressionable, encounter with three young Russian men. “The Birthday Party” recalls a wild evening at the home of her close friend, showing how the Russians greet special occasions. Both the third and fourth essays take place in Moscow, where Amanda returns to visit old friends. These two essays portray the lives of the new economic elite in comparison with the average citizen, as well as show how young Russians face the new challenges that greet them. "Politics Russian Style" recalls a political rally in St. Petersburg, and attempts to shed light on the wacky political world of an infant democracy. Chapters Six through Ten take place away from the western cities of St. Petersburg and Moscow, as Amanda brings us to the cold, mysterious land of Siberia in the dead of winter. She recounts her five day train ride with a retired, high-powered, Communist party official, her experiences in the provincial city of Irkutsk, and a brief trip to a Buddhist monastery and, later, an excursion to Lake Baikal. Back in St. Petersburg, Chapter Eleven gives a humorous account of a ski trip with several Russian friends. Amanda finishes her work with her final chapter, “The Dacha," which describes a weekend spent at a Russian country home with her friend's family.

Bayesian analysis of extreme events with threshold estimation

The aim of this paper is to analyze extremal events using Generalized Pareto Distributions (GPD), considering explicitly the uncertainty about the threshold. Current practice empirically determines this quantity and proceeds by estimating the GPD parameters based on data beyond it, discarding all the information available be10w the threshold. We introduce a mixture model that combines a parametric form for the center and a GPD for the tail of the distributions and uses all observations for inference about the unknown parameters from both distributions, the threshold inc1uded. Prior distribution for the parameters are indirectly obtained through experts quantiles elicitation. Posterior inference is available through Markov Chain Monte Carlo (MCMC) methods. Simulations are carried out in order to analyze the performance of our proposed mode1 under a wide range of scenarios. Those scenarios approximate realistic situations found in the literature. We also apply the proposed model to a real dataset, Nasdaq 100, an index of the financiai market that presents many extreme events. Important issues such as predictive analysis and model selection are considered along with possible modeling extensions.