Phi-Divergence Statistics for Testing Linear Hypotheses in Logistic Regression Models

In this paper we introduce and study two new families of statistics for the problem of testing linear combinations of the parameters in logistic regression models. These families are based on the phi-divergence measures. One of them includes the classical likelihood ratio statistic and the other the classical Pearson's statistic for this problem. It is interesting to note that the vector of unknown parameters, in the two new families of phi-divergence statistics considered in this paper, is estimated using the minimum phi-divergence estimator instead of the maximum likelihood estimator. Minimum phi-divergence estimators are a natural extension of the maximum likelihood estimator.     

Exit is the answer: The political nature of Central American migration

This article provides evidence that many Central Americans who have joined the migrant caravans to the north manifest a profound discontent with the political institutions of their home countries. It is based on surveys with migrants in refugee centres, compared with similar data from the AmericasBarometer survey, and complemented with contextual qualitative data on the experience of immigrants passing through Mexico. The article shows that several Central Americans in route to the north do not trust their political institutions and express little support for their political system. It demonstrates that in contexts where economic instability, rampant crime, and environmental uncertainty prevail, many citizens keep exiting their countries under the conviction that government institutions have lost the capability to protect them from existential threats.     

Mapping Our Way: New Formations in Technical Services: Ohio Valley Group of Technical Services Librarians Annual Conference

Abstract

The annual meeting of the Ohio Valley Group of Technical Services Librarians (OVGTSL) was held May 16–18, 2007, at the Holiday Inn-University Plaza in Bowling Green, Kentucky. One hundred twenty technical services librarians from Indiana, Ohio, Kentucky, and points beyond gathered for programming centered around the theme of “Mapping Our Way: New Formations in Technical Services.”     

Convergence criteria for interval-valued inequality indices

In this paper we introduce an interval-valued inequality index for random intervals based on a convex function. We show that if this function does not grow faster than x ^p , then the inequality index is continuous on the space of random intervals with finite p-th moment. A bound for the distance between the inequality indices of two random intervals is also constructed. An example is presented to motivate and illustrate the developments in this paper.     

On the Bayesian Estimation for the Uniform Scale Parameter via a Functional Equation

Bayes uniform model under the squared error loss function is shown to be completely identifiable by the form of the Bayes estimates of the scale parameter. This results in solving a specific functional equation. A complete characterization of differentiable Bayes estimators (BE) and generalized Bayes estimators (GBE) is given as well as relations between degrees of smoothness of the estimators and the priors. Characterizations of strong (generalized Bayes) Bayes sequence (SBS or SGBS) are also investigated. A SBS is a sequence of estimators (one for each sample size) where all its components are BE generated by the same prior measure. A complete solution is given for polynomial Bayesian estimation.     

Chisquared and related inducing pivot variables: an application to orthogonal mixed models

Abstract

We use chi-squared and related pivot variables to induce probability measures for model parameters, obtaining some results that will be useful on the induced densities. As illustration we considered mixed models with balanced cross nesting and used the algebraic structure to derive confidence intervals for the variance components. A numerical application is presented.     

Multivariate thin plate spline estimates for the posterior probabilities in the classification problem

A nonparametric estimate for the posterior probabilities in the classification problem using multivariate thin plate splines is proposed. This method presents a nonpararnetric alternative to logistic discrimination as well as to survival curve estimation. The degree of smoothness of the estimate is determined from the data using generalized crossvalidation.     

Analyzing Small Samples of Repeated Measures Data with the Mixed-Model Adjusted F Test

This research examines the Type I error rates obtained when using the mixed model with the Kenward-Roger correction and compares them with the Between–Within and Satterthwaite approaches in split-plot designs. A simulated study was conducted to generate repeated measures data with small samples under normal distribution conditions. The data were obtained via three covariance matrices (unstructured, heterogeneous first-order auto-regressive, and random coefficients), the one with the best fit being selected according to the Akaike criterion. The results of the simulation study showed the Kenward-Roger test to be more robust, particularly when the population covariance matrices were unstructured or heterogeneous first-order auto-regressive. The main contribution of this study lies in showing that the Kenward–Roger method corrects the liberal Type I error rates obtained with the Between–Within and Satterthwaite approaches, especially with positive pairings between group sizes and covariance matrices.     

A variability taxonomy to support automation decision-making for manufacturing processes

Abstract

Although many manual operations have been replaced by automation in the manufacturing domain in various industries, skilled operators still carry out critical manual tasks such as final assembly. The business case for automation in these areas is difficult to justify due to increased complexity and costs arising out of process variabilities associated with those tasks. The lack of understanding of process variability in automation design means that industrial automation often does not realize the full benefits at the first attempt, resulting in the need to spend additional resource and time, to fully realize the potential. This article describes a taxonomy of variability when considering the automation of manufacturing processes. Three industrial case studies were analyzed to develop the proposed taxonomy. The results obtained from the taxonomy are discussed with a further case study to demonstrate its value in supporting automation decision-making.     

Mapping Our Way: New Formations in Technical Services: Ohio Valley Group of Technical Services Librarians Annual Conference

The annual meeting of the Ohio Valley Group of Technical Services Librarians (OVGTSL) was held May 16–18, 2007, at the Holiday Inn-University Plaza in Bowling Green, Kentucky. One hundred twenty technical services librarians from Indiana, Ohio, Kentucky, and points beyond gathered for programming centered around the theme of “Mapping Our Way: New Formations in Technical Services.”