A simple estimator for a shared frailty regression model

Summary. We propose a simple estimation procedure for a proportional hazards frailty regression model for clustered survival data in which the dependence is generated by a positive stable distribution. Inferences for the frailty parameter can be obtained by using output from Cox regression analyses. The computational burden is substantially less than that of the other approaches to estimation. The large sample behaviour of the estimator is studied and simulations show that the approximations are appropriate for use with realistic sample sizes. The methods are motivated by studies of familial associations in the natural history of diseases. Their practical utility is illustrated with sib pair data from Beaver Dam, Wisconsin.     

Nonparametric estimation of the conditional distribution function in a semiparametric censorship model

In this paper we propose a new nonparametric estimator of the conditional distribution function under a semiparametric censorship model. We establish an asymptotic representation of the estimator as a sum of iid random variables, balanced by some kernel weights. This representation is used for obtaining large sample results such as the rate of uniform convergence of the estimator, or its limit distributional law. We prove that the new estimator outperforms the conditional Kaplan–Meier estimator for censored data, in the sense that it exhibits lower asymptotic variance. Illustration through real data analysis is provided.     

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.     

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.