Estimating ordered parameters by linear programming

There are many models that require the estimation of a set of ordered parameters. For example, multivariate analysis of variance often is formulated as testing for the equality of the parameters versus an ordered alternative. This problem, referred to as isotonic inference, constrained inference, or isotonic regression, has led to the development of general solutions, not often easy to apply in special models. In this expository paper, we study the special case of a separable convex quadratic programming problem for which the optimality conditions lead to a readily solved linear complementarity problem in the Lagrange multipliers, and subsequently to an equivalent linear programming problem, whose solution can be used to recover the solution of the original isotonic problem. The method can be applied to estimating ordered correlations, ordered binomial probabilities, ordered Poisson parameters, ordered exponential scale parameters, or ordered risk differences.     

Asthma Patients' Activities and Air Pollution: A Semiparametric Censored Regression Analysis

Asthma patients' health status may be especially sensitive to some types of air pollution, but the evidence on this is mixed. We explore the effects of ground-level ozone on asthma patient's activities, breaking apart the usual aggregated category of leisure into indoor and outdoor activities, and differentiating those by whether the activities were active or inactive. Applying the semiparametric censored estimation method we demonstrate that even though the period over which activities were observed was relatively low in ozone levels, there is a significant impact of ozone on a few activities. The (non-ozone) economic and demographic variables in the model play significant roles in explaining the allocation of time among seven activities, suggesting the suitability of the approach for other household decision-making contexts.     

The Development of Affect Specificity in Infants' Use of Emotion Cues

This study examined the emergence of affect specificity in infancy. In this study, infants received verbal and facial signals of 2 different, negatively valenced emotions (fear and sadness) as well as neutral affect via a television monitor to determine if they could make qualitative distinctions among emotions of the same valence. Twenty 12‐ to 14‐month‐olds and 20 16‐ to 18‐month‐olds were examined. Results suggested that younger infants showed no evidence of referential specificity, as they responded similarly to both the target and distracter toys, and showed no evidence of affect specificity, showing no difference in play between affect conditions. Older infants, in contrast, showed evidence both of referential and affect specificity. With respect to affect specificity, 16‐ to 18‐month‐olds touched the target toy less in the fear condition than in the sad condition and showed a larger proportion of negative facial expressions in the sad condition versus the fear condition. These findings suggest a developmental emergence after 15 months of age for affect specificity in relating emotional messages to objects.     

Modeling External Risks in Project Management

To ascertain the viability of a project, undertake resource allocation, take part in bidding processes, and other related decisions, modern project management requires forecasting techniques for cost, duration, and performance of a project, not only under normal circumstances, but also under external events that might abruptly change the status quo. We provide a Bayesian framework that provides a global forecast of a project's performance. We aim at predicting the probabilities and impacts of a set of potential scenarios caused by combinations of disruptive events, and using this information to deal with project management issues. To introduce the methodology, we focus on a project's cost, but the ideas equally apply to project duration or performance forecasting. We illustrate our approach with an example based on a real case study involving estimation of the uncertainty in project cost while bidding for a contract.     

New Labour and youth justice

The paper discusses the reasons for the large amount of critical commentary that New Labour's reforms of the youth justice system have attracted. It explores the extent to which there is something ‘new’ about these reforms, suggesting that there are important differences when New Labour's approach is compared with its predecessor's. It then discusses the main lines of critical commentary on the reforms, concluding that much of it is over‐abstract and insufficiently empirically informed. The paper concludes with some ambiguous evidence on what the impact of the reforms has actually been. Copyright © 2003 John Wiley & Sons, Ltd.     

General Job Satisfaction From a Developmental Perspective: Exploring Choice—Job Matches at Two Career Stages

The authors explored predictions of general job satisfaction at early and middle adulthood and uncovered several findings about developmental processes associated with job satisfaction. Tests of life‐span career theory propositions revealed that neither choice‐job congruence nor gender added significantly to predictions of job satisfaction at 2 career stages. Earlier occupational choice and current job added to predictions of midcareer (modal age 43 years) job satisfaction, especially for men. The predictability of job satisfaction is apparently influenced by the career stage when satisfaction is appraised.     

Which Wald statistic? Choosing a parameterization of the Wald statistic to maximize power in k-sample generalized estimating equations

The Wald statistic is known to vary under reparameterization. This raises the question: which parameterization should be chosen, in order to optimize power of the Wald statistic? We specifically consider k-sample tests of generalized linear models (GLMs) and generalized estimating equations (GEEs) in which the alternative hypothesis contains only two parameters. An example is presented in which such an alternative hypothesis is of interest. Amongst a general class of parameterizations, we find the parameterization that maximizes power via analysis of the non-centrality parameter, and show how the effect on power of reparameterization depends on sampling design and the differences in variance across samples. There is no single parameterization with optimal power across all alternatives. The Wald statistic commonly used under the canonical parameterization is optimal in some instances but it performs very poorly in others. We demonstrate results by example and by simulation, and describe their implications for likelihood ratio statistics and score statistics. We conclude that due to poor power properties, the routine use of score statistics and Wald statistics under the canonical parameterization for GEEs is a questionable practice.     

The risky business of insurance pricing

The factors influencing insurance pricing decisions are assessed using the ISO product liability ratemaking files for 1980–1984. The mean loss level has a strong positive effect on manual rates and premium rates/exposure. Evidence on a variety of ambiguity measures is more mixed. As a broad generalization, risk ambiguity lowers manual rates, which may reflect exclusion of large loss outliers as being unrepresentative. Risk ambiguity tends to have a positive effect on actual pricing decisions for particular policies, especially bodily injury lines and the interactive risk-ambiguity model.     

A note on estimating regression coefficients with missing data

In this note, we consider the problem of estimating regression coefficients when there are missing observations of some explanatory variables. Following Dagenais (1973), Gourieroux and Monfort (1981), and Conniffe (1983a, 1983b), we assume auxiliary relationships exist among explanatory varibles. Several estimatprs and their interrelationships are discussed. We begin with the model of Gourieroux and

Monfort (1981)