Estimates of per Capita Fish Consumption in the U.S. Based on the Continuing Survey of Food Intake by Individuals (CSFII)

This paper presents estimates of daily average per capita fish consumption by age and gender for the 48 conterminous states. The estimated consumption rates are reported for three fish habitats: freshwater/estuarine fish, marine fish, and all fish. The estimates were generated from the combined 1989, 1990, and 1991 Continuing Survey of Food Intake by Individuals (CSFII), a national food consumption survey conducted by the United States Department of Agriculture (USDA). Point and interval estimates of per capita fish consumption were generated from the empirical distribution of daily average per capita consumption. The point estimates include the mean, 50th, 75th, 90th, 95th, and 99th percentiles. Ninety percent confidence intervals are provided for the estimated mean and 90% bootstrap intervals are provided for percentile estimates. Information in a recipe file provided by USDA was used to calculate the amount of fish in recipes which contain fish. The estimated consumption rates are based on the weight of fish in its prepared or "as consumed" condition. The estimated mean consumption rate for all fish for the U.S. population of the 48 conterminous states was 15.65 grams/person/day (C.I.:14.67–16.63) of which 4.71 grams/person/day (C.I.:4.17–5.25) was freshwater/estuarine fish and 10.94 grams/person/day (C.I.: 10.14–11.73) was marine fish.     

Review Essay:Rural Sociology,Migration, and Community Change

Research in Rural Sociology and Development: Focus on Migration, edited by Harry K. Schwarzweller and Brendan P. Mullan. Population Change in the Rural West: 1975–1990, edited by John M. Wardwell and James H. Copp. Lanham, MD Community of Strangers: Change, Turnover, Turbulence and the Transformation of a Midwestern Country Town, by Joseph A. Amato and John Radzilowski.     

Sparse estimation and inference for censored median regression

Censored median regression has proved useful for analyzing survival data in complicated situations, say, when the variance is heteroscedastic or the data contain outliers. In this paper, we study the sparse estimation for censored median regression models, which is an important problem for high dimensional survival data analysis. In particular, a new procedure is proposed to minimize an inverse-censoring-probability weighted least absolute deviation loss subject to the adaptive LASSO penalty and result in a sparse and robust median estimator. We show that, with a proper choice of the tuning parameter, the procedure can identify the underlying sparse model consistently and has desired large-sample properties including root-n consistency and the asymptotic normality. The procedure also enjoys great advantages in computation, since its entire solution path can be obtained efficiently. Furthermore, we propose a resampling method to estimate the variance of the estimator. The performance of the procedure is illustrated by extensive simulations and two real data applications including one microarray gene expression survival data.     

Different and unequal: the educational segregation of Roma pupils in Europe

This article analyses and welcomes the decision of the Grand Chamber of the European Court of Human Rights which held that the use of special schools for Roma pupils was contrary to the right to an education coupled with the prohibition on discrimination. The decision has wide ramifications for the education of minority, particularly Roma, pupils who are often sent to remedial schools or special classes as an alternative to mainstream, integrated education. It is argued that such segregation, whilst it may arise from a legitimate intention to address educational disadvantage, cannot achieve such a goal in a climate of separation and intolerance which permeates the wider society. The Grand Chamber’s willingness to scrutinise the wider societal context and to allow statistical evidence to suggest a prime facie case of indirect discrimination, will be welcomed by those seeking a more pro‐active non‐discrimination platform from the European Court of Human Rights (ECHR).     

Understanding Management Performance

Current models of the factors underlying management performance make use of a variety of variables at different levels of analysis. A framework is presented in which variables of three different types are linked together. Using data from a sample (n = 437) of British managers this article explores relationships between personality factors (using the big-five factors), work competencies and managerial performance. Results from the analyses reveal a set of underlying competency factors, which show different patterns of correlation with two facets of performance: current proficiency and promotability. In turn, these factors and the facets of performance show relationships with the big-five personality factors. Current proficiency is more closely related to competencies of organization, specialization and analysis – competencies more likely to be displayed by people who are conscientious and introverted. Promotability is linked more closely to competencies concerning action/motivation, flexibility/sensitivity and communication – competencies more likely to be displayed by people who are extroverted with lower conscientiousness and agreeableness.     

Incorporation of historical controls using semiparametric mixed models

The analysis of animal carcinogenicity data is complicated by various statistical issues. A topic of recent debate is how to control for the effect of the animal's body weight on the outcome of interest, the onset of tumours. We propose a method which incorporates historical information from the control animals in previously conducted experiments. We allow non-linearity in the effects of body weight by modelling the relationship nonparametrically through a penalized spline. A simple extension of the penalized spline model allows the relationship between weight and the onset of tumour to vary from one experiment to another.