A Sparse Implementation of the Average Information Algorithm for Factor Analytic and Reduced Rank Variance Models

Factor analytic variance models have been widely considered for the analysis of multivariate data particularly in the psychometrics area. Recently Smith, Cullis & Thompson (2001) have considered their use in the analysis of multi‐environment data arising from plant improvement programs. For these data, the size of the problem and the complexity of the variance models chosen to account for spatial heterogeneity within trials implies that standard algorithms for fitting factor analytic models can be computationally expensive. This paper presents a sparse implementation of the average information algorithm (Gilmour, Thompson & Cullis, 1995) for fitting factor analytic and reduced rank variance models.     

Optimal scaling of Metropolis algorithms: Heading toward general target distributions

The authors provide an overview of optimal scaling results for the Metropolis algorithm with Gaussian proposal distribution. They address in more depth the case of high‐dimensional target distributions formed of independent, but not identically distributed components. They attempt to give an intuitive explanation as to why the well‐known optimal acceptance rate of 0.234 is not always suitable. They show how to find the asymptotically optimal acceptance rate when needed, and they explain why it is sometimes necessary to turn to inhomogeneous proposal distributions. Their results are illustrated with a simple example.     

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.     

Some results on optimality in models with heteroscedastic errors from partial optimum designs

This paper studies optimum designs for linear models when the errors are heteroscedastic. Sufficient conditions are given in order to obtainD-, A- andE-optimum designs for a complete regression model from partial optimum designs for some sub-parameters. A result about optimality for a complete model from the optimality for the submodels is included. Supported by Junta de Andalucía, research group FQM244.     

A “brer rabbit” case for reverse mandated benefits

Reverse mandated benefits is a government-mandated policy that requires employees to provide their employers with benefits that workers would not provide otherwise. Of course, only those benefits would be mandated that are worth more to employers than they cost, as determined by political authorities. My case for such a policy argues that it is at least as sensible as policies mandating that employers provide benefits to their employees that would not be provided otherwise.     

Intertemporal choice under timing risk: An experimental approach

This paper investigates how individuals evaluate delayed outcomes with risky realization times. Under the discounted expected utility (DEU) model, such evaluations depend only on intertemporal preferences. We obtain several testable hypotheses using the DEU model as a benchmark and test these hypotheses in three experiments. In general, our results show that the DEU model is a poor predictor of intertemporal choice behavior under timing risk. We found that individuals are averse to timing risk and that they evaluate timing lotteries in a rank-dependent fashion. The main driver of timing risk aversion is nothing but probabilistic risk aversion that stems from the nonlinear treatment of probabilities.     

The availability of personal and external coping resources: Thier impact on job stress and employee attitudes during organizational restructuring

This study examines the relationships among personal coping resources, social support, external coping resources, job stressors and job strains in a sample of 110 American Telephone and Telegraph employees undergoing a major organizational restructuring. The study expanded on a model suggested by Ashford (1988) by defining another category of coping resources that employees may draw upon to deal with the stressors and strains which occur during major organizational changes. External coping resources were defined as those which provided employees with a sense of 'vicarious control' in stressful situations. Results indicated that personal coping resources, social support and external coping resources had a direct effect upon job stressor and strain levels. No 'buffering' effect of these coplng resources was found. Hierarchical regression analyses indicated that external coping resources added to the prediction of job stressors and strains even when pertonal coping resources and social support were entered first into the prediction questions.     

Making ends meet: perceptions of poverty in Sweden

During the era after the Second World War, Sweden has built a welfare system based on labor market participation and income maintenance. Low unemployment and decent wages are supposed to guarantee people a labor market income or income maintenance, which in turn should provide a proper standard for everyone. However, a rapid increase in unemployment and economic problems have made the future of the Swedish welfare state more uncertain than ever. These circumstances have, among other things, led to the suggestion that Sweden should abandon the income maintenance policy and create a social policy system with the more limited ambition of guaranteeing everyone a minimum income. In that case, one central question must be answered: what constitutes a decent minimum income in today's Sweden? Where should we draw the poverty line under which people will not be forced to live? These questions are central in the current debate. The consensual poverty line method is used in this article to derive a poverty line relevant for today's Sweden. The results shows that more than every fifth household has an income below the consensual poverty line. That is, they have an income that most Swedes would argue is too low to make ends meet. The level of the consensual poverty line was compared with the National Board of Health and Welfare's guidelines for social assistance. The consensual poverty line was shown to be more generous to small households and the norm for social assistance was more generous to larger households. Finally, the expenditure for guaranteeing all Swedish household a minimum income equal to the consensual poverty line was estimated: more than SEK 25 billion per year. The results in the article casts serious doubt on the ability of the Swedish welfare state to secure a decent income to all citizens.     

A modified false discovery rate multiple-comparisons procedure for discrete data, applied to human immunodeficiency virus genetics

Summary.  To help to design vaccines for acquired immune deficiency syndrome that protect broadly against many genetic variants of the human immunodeficiency virus, the mutation rates at 118 positions in HIV amino-acid sequences of subtype C versus those of subtype B were compared. The false discovery rate (FDR) multiple-comparisons procedure can be used to determine statistical significance. When the test statistics have discrete distributions, the FDR procedure can be made more powerful by a simple modification. The paper develops a modified FDR procedure for discrete data and applies it to the human immunodeficiency virus data. The new procedure detects 15 positions with significantly different mutation rates compared with 11 that are detected by the original FDR method. Simulations delineate conditions under which the modified FDR procedure confers large gains in power over the original technique. In general FDR adjustment methods can be improved for discrete data by incorporating the modification proposed.