Robustness measures for Bayes linear analyses

We consider the role of global robustness measures in Bayes linear analysis. We suggest two such measures, one for expectation comparisons and one for variance comparisons. Geometric interpretations of the measures are presented. The approach is illustrated by considering the robustness of certain multiplicative models to assumptions of independence, with particular application to a problem arising in an asset management model for water resources.     

Measuring educational standards

Every summer, when English public examination results appear, there is a debate within the media about whether "educational standards" are changing. Harvey Goldstein argues that much of what passes for informed debate in the English media is both irrelevant and ill informed, and that there is no purely objective, statistical, means for measuring changes in "standards".     

Self-disclosure in treatment: What therapists do and don't talk about

In contrast to the traditional view that sees therapist self-disclosure as a form of countertransference acting-out that either makes the therapeutic process more difficult or subverts it completely, this paper will present a self psychological rationale for the selected use of therapist self-disclosure in treatment. It will discuss the nature of therapist self-disclosure, issues in its use, countertransference issues, and its evaluation.     

A novel bootstrap procedure for assessing the relationship between class size and achievement

Summary. There is on-going concern about the relationship between class size and achievement for children in their first years of schooling. The Institute of Education's class size project was set up to address this issue and began recruiting in the autumn of 1996. However, because of the non-normality of achievement measures, especially in mathematics, the results have hitherto been presented by using transformed achievement measures. This makes the interpretation difficult for non-statisticians. Ideally, the data would be modelled on the original scale and a bootstrap procedure used to ensure that inferences are robust to non-normality. However, the data are multilevel. In the paper we therefore propose a nonparametric residual bootstrap procedure that is suitable for multilevel models, show that it is consistent and present a simulation study which demonstrates its potential to yield substantial reductions in the difference between nominal and actual confidence interval coverage, compared with a parametric bootstrap, when the underlying distribution of the data is non-normal. We then apply our approach to estimate the relationship between class size and achievement for children in their reception year, after adjusting for other possible determinants.     

A Cohort Model of Fertility Postponement

We introduce a new formal model in which demographic behavior such as fertility is postponed by differing amounts depending only on cohort membership. The cohort-based model shows the effects of cohort shifts on period fertility measures and provides an accompanying tempo adjustment to determine the period fertility that would have occurred without postponement. Cohort-based postponement spans multiple periods and produces “fertility momentum,” with implications for future fertility rates. We illustrate several methods for model estimation and apply the model to fertility in several countries. We also compare the fit of period-based and cohort-based shift models to the recent Dutch fertility surface, showing how cohort- and period-based postponement can occur simultaneously.     

Relationships between period and cohort life expectancy: Gaps and lags

This paper offers an empirical and analytic foundation for regarding period life expectancy as a lagged indicator of the experience of real cohorts in populations experiencing steady improvement in mortality. We find that current period life expectancy in the industrialized world applies to cohorts born some 40–50 years ago. Lags track an average age at which future years of life are being gained, in a sense that we make precise. Our findings augment Ryder's classic results on period–cohort translation.     

Preliminary Inspection of Multivariate Data

A simple approach to the direct inspection of multivariate data is discussed in the context of a specific data set.     

Explaining Anomalous High Performance in a Health Care Supply Chain*

An implicit assumption in distributing and coordinating work among independent organizations in a supply chain is that a focal organization can use financial or contractual mechanisms to enforce compliance among the other organizations in meeting desired performance objectives. Absent contractual agreement or financial gain, there is little incentive for independent organizations to coordinate their process improvement activities. In this study, we examine a health care supply chain in which the work is distributed among independent organizations. We use a detailed case study and an abductive reasoning approach to understand how and why the independent organizations choose to coordinate and collaborate in their work. Our study makes two contributions to the literature. First, we use well‐established lean principles to explain how independent organizations achieve superior performance despite highly uncertain and variable customer demand—a context considerably different from the origins of lean principles. Second, we forward relational coordination theory to explain why the organizations in this decentralized supply chain coordinate their work. Relational coordination includes the use of shared goals, shared knowledge, and mutual respect for one another's work as primary mechanisms to explain process improvement in the absence of any contractual incentives. Our study constitutes a first step in generating theory for work design and its improvement in decentralized supply chains.