A Weighted Composite Dose – Response Model For Human Salmonellosis

This article describes the development of a weighted composite dose – response model for human salmonellosis. Data from previously reported human challenge studies were categorized into two different groups representing low and moderately virulent/pathogenic Salmonella strains based on a disease end point. Because epidemiological data indicate that some Salmonella strains are particularly pathogenic, and in the absence of human feeding study data for such strains, Shigella dysenteriae was used as a proxy for highly virulent strains. Three single-hit dose – response models were applied to the human feeding study data and evaluated for best fit using maximum likelihood estimation: (1) the exponential (E-1pop), (2) the two-subpopulation exponential (E-2pop), and (3) the Beta-Poisson (BP). Based on the goodness-of-fit test, the E-1pop and BP were the best-fit models for low and moderately virulent/pathogenic Salmonella strains, and the E-2pop and BP models were better for highly virulent/pathogenic strains. Epistemic analysis was conducted by determining the degree of confidence associated with the selected models, which was found to be 50%/50% (E-1pop/BP) for low and moderately pathogenic Salmonella strains, and 9.8%/90.2% (E-2pop/BP) for highly virulent strains. The degree of confidence for each component model and variations in the proportion of strains within each virulence/pathogenicity category were incorporated into the overall composite model. This study describes the influence of variation in strain virulence and host susceptibility on the shape of the population dose – response relationship.     

Organizational Changes and Job Satisfaction among Support Staff

ABSTRACT

The purpose of this study is to identify job satisfaction amongst support staff employed by a nonprofit company undergoing organizational changes. The Job Satisfaction Survey (JSS) scale was used to measure overall job satisfaction and was conducted among 38 workers and the data was analyzed using content analysis. The findings indicate that workers were satisfied with some sections of their job but also dissatisfied with some others, scoring an average job satisfaction amongst the participating groups. Factors such as good relations with colleagues, training opportunities, and work flexibility were identified to assist with increasing worker satisfaction. Further suggestions for enhancing employees’ job satisfaction are provided.     

A Discrete Variable Chain Graph for Applicants for Credit

A bank offering unsecured personal loans may be interested in several related outcome variables, including defaulting on the repayments, early repayment or failing to take up an offered loan. Current predictive models used by banks typically consider such variables individually. However, the fact that they are related to each other, and to many interrelated potential predictor variables, suggests that graphical models may provide an attractive alternative solution. We developed such a model for a data set of 15 variables measured on a set of 14 000 applications for unsecured personal loans. The resulting global model of behaviour enabled us to identify several previously unsuspected relationships of considerable interest to the bank. For example, we discovered important but obscure relationships between taking out insurance, prior delinquency with a credit card and delinquency with the loan.     

Bayesian estimation for the Pareto income distribution

The Bayes estimators of the Gini index, the mean income and the proportion of the population living below a prescribed income level are obtained in this paper on the basis of censored income data from a pareto income distribution. The said estimators are obtained under the assumptions of a two-parameter exponential prior distribution and the usual squared error loss function. This work is also extended to the case when the income data are grouped and the exact incomes for the individuals in the population are not available. The method for the assessment of the hyperparameters is also outlined. Finally, the results are generalized for the doubly truncated gamma prior distribution. Now deceased.     

Long-term Success of Adaptation Strategies: Evidence from Finnish Companies

This study analyses the success of adaptation strategies applied by Finnish companies during the recession in 1989–93. Five different strategies emerged from data gleaned from a questionnaire answered by 750 companies. In the medium term, investment in new product development and marketing and in the acquisition of new customers was the most successful strategy while a strategy heavily based on negotiating finance contracts and restructuring was the most unsuccessful. To evaluate the long-term effects of adopted strategies, financial statements from 644 companies in 1994 and 1997 were analysed. The results supported the medium-term conclusions. In general, they suggested that in the long-term, active adaptation strategies are most likely to lead to sustained success whereas passive (financial) strategies are associated with a high risk of failure.     

Quantitative Methods for Environmental Justice Assessment of Transportation

Application of Executive Order 12898 to risk assessment of highway or rail transport of hazardous materials has proven difficult; in general, the location and conditions affecting the propagation of a plume of hazardous material released in a potential accident are unknown. Therefore, analyses have only been possible in a geographically broad or approximate manner. The advent of geographic information systems and development of software enhancements at Sandia National Laboratories have made kilometer-by-kilometer analysis of populations tallied by U.S. Census blocks along entire routes practicable. Tabulations of total or racially/ethnically distinct populations close to a route, its alternatives, or the broader surrounding area, can then be compared and differences evaluated statistically. This article presents methods of comparing populations and their racial/ethnic compositions using simple tabulations, histograms, and chi-square tests for statistical significance of differences found. Two examples of these methods are presented: comparison of two routes and comparison of a route with its surroundings.     

Smoothed estimates for nonlinear time series models with irregular data

Time series data observed at unequal time intervals (irregular data) occur quite often and this usually poses problems in its analysis. A recursive form of the exponentially smoothed estimated is here proposed for a nonlinear model with irregularly observed data and its asymptotic properties are discussed An alternative smoother to that of Wright (1985) is also derived. Numerical comparison is made between the resulting estimates and other smoothed estimates.