Bayesian disclosure risk assessment: predicting small frequencies in contingency tables

Summary.  We propose an approach for assessing the risk of individual identification in the release of categorical data. This requires the accurate calculation of predictive probabilities for those cells in a contingency table which have small sample frequencies, making the problem somewhat different from usual contingency table estimation, where interest is generally focused on regions of high probability. Our approach is Bayesian and provides posterior predictive probabilities of identification risk. By incorporating model uncertainty in our analysis, we can provide more realistic estimates of disclosure risk for individual cell counts than are provided by methods which ignore the multivariate structure of the data set.     

Job relocation: Stress and the role of the family

Job relocation is an accepted feature of the career structure for an ever increasing number of employees. Moving from one work environment to another, coupled with relocating the family, can induce stress and so influence performance at work. This paper reviews the available evidence concerning possible roles the family may play in the relocation process. It is argued that a systemic approach is ideally suited to unravelling the complex relationship between work and home environments that underlies the process of individual and family adaptation to relocation. This relationship must be understood in order to provide constructive advice to employers concerning effective relocation policies.