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.     

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)     

Modeling for Risk Assessment of Neurotoxic Effects

The regulation of noncancer toxicants, including neurotoxicants, has usually been based upon a reference dose (allowable daily intake). A reference dose is obtained by dividing a no-observed-effect level by uncertainty (safety) factors to account for intraspecies and interspecies sensitivities to a chemical. It is assumed that the risk at the reference dose is negligible, but no attempt generally is made to estimate the risk at the reference dose. A procedure is outlined that provides estimates of risk as a function of dose. The first step is to establish a mathematical relationship between a biological effect and the dose of a chemical. Knowledge of biological mechanisms and/or pharmacokinetics can assist in the choice of plausible mathematical models. The mathematical model provides estimates of average responses as a function of dose. Secondly, estimates of risk require selection of a distribution of individual responses about the average response given by the mathematical model. In the case of a normal or lognormal distribution, only an estimate of the standard deviation is needed. The third step is to define an adverse level for a response so that the probability (risk) of exceeding that level can be estimated as a function of dose. Because a firm response level often cannot be established at which adverse biological effects occur, it may be necessary to at least establish an abnormal response level that only a small proportion of individuals would exceed in an unexposed group. That is, if a normal range of responses can be established, then the probability (risk) of abnormal responses can be estimated. In order to illustrate this process, measures of the neurotransmitter serotonin and its metabolite 5-hydroxyindoleacetic acid in specific areas of the brain of rats and monkeys are analyzed after exposure to the neurotoxicant methylene-dioxymethamphetamine. These risk estimates are compared with risk estimates from the quantal approach in which animals are classified as either abnormal or not depending upon abnormal serotonin levels.     

Summary of the Workshop on Issues in Risk Assessment: Quantitative Methods for Developmental Toxicology

This report summarizes the proceedings of a conference on quantitative methods for assessing the risks of developmental toxicants. The conference was planned by a subcommittee of the National Research Council's Committee on Risk Assessment Methodology ⁴ in conjunction with staff from several federal agencies, including the U.S. Environmental Protection Agency, U.S. Food and Drug Administration, U.S. Consumer Products Safety Commission, and Health and Welfare Canada. Issues discussed at the workshop included computerized techniques for hazard identification, use of human and animal data for defining risks in a clinical setting, relationships between end points in developmental toxicity testing, reference dose calculations for developmental toxicology, analysis of quantitative dose-response data, mechanisms of developmental toxicity, physiologically based pharmacokinetic models, and structure-activity relationships. Although a formal consensus was not sought, many participants favored the evolution of quantitative techniques for developmental toxicology risk assessment, including the replacement of lowest observed adverse effect levels (LOAELs) and no observed adverse effect levels (NOAELs) with the benchmark dose methodology.     

Significance of the Dermal Route of Exposure to Risk Assessment

The skin is a route of exposure that needs to be considered when conducting a risk assessment. It is necessary to identify the potential for dermal penetration by a chemical as well as to determine the overall importance of the dermal route of exposure as compared with inhalation or oral routes of exposure. The physical state of the chemical, vapor or liquid, the concentration, neat or dilute, and the vehicle, lipid or aqueous, is also important. Dermal risk is related to the product of the amounts of penetration and toxicity. Toxicity involves local effects on the skin itself and the potential for systemic effects. Dermal penetration is described in large part by the permeability constant. When permeability constants are not known, partition coefficients can be used to estimate a chemical's potential to permeate the skin. With these concepts in mind, a tiered approach is proposed for dermal risk assessment. A key first step is the determination of a skin-to-air or skin-to-medium partition coefficient to estimate a potential for dermal absorption. Building a physiologically-based pharmacokinetic (PBPK) model is another step in the tiered approach and is useful prior to classical in vivo toxicity tests. A PBPK model can be used to determine a permeability constant for a chemical as well as to show the distribution of the chemical systemically. A detailed understanding of species differences in the structure and function of the skin and how they relate to differences in penetration rates is necessary in order to extrapolate animal data from PBPK models to the human. A study is in progress to examine anatomical differences for four species.     

Who Gets What From Government? Distributional Consequences of Child‐Care Assistance Policies

Given the fragmented structure of child‐care assistance in the United States, it has been difficult to obtain accurate estimates of which families are assisted, through which mechanisms, and at what level. Making use of survey data from New York City, we analyze the distribution of several forms of public child‐care assistance. Results suggest that about 40% of all families with young children receive some form of child‐care assistance. Considering all forms of assistance, the distribution of child‐care help is targeted in both expected and some unexpected ways. Implications of these results are discussed in the context of U.S. child‐care policies governing access and benefit levels.