Phthalate Exposure Through Food and Consumers' Risk Perception of Chemicals in Food

Phthalates have been detected in various types of retail foods. Consumers' exposure to phthalates is common. Consumers are concerned about chemicals in food. Our aim was to investigate the relationships between consumers' exposure to phthalates through food, consumers' interest in a natural and healthy diet, risk perception of food chemicals, and consumers' diet patterns. We collected data through a mail survey in the adult Swiss-German population ( N  = 1,200). We modeled exposure to di(2-ethylhexyl) phthalate (DEHP), dibutyl phthalate (DBP), benzyl butyl phthalate (BBP), and diethyl phthalate (DEP) based on a food frequency questionnaire and phthalate concentrations reported from food surveys. Using rating scales, we assessed risk perceptions of chemicals in food and interest in a natural and healthy diet. Higher risk perceptions and higher natural and healthy diet interest were associated with higher daily doses of DEHP, BBP, and DEP. No health risk from phthalates in food was identified for the vast majority of the population. Four consumers' diet clusters were discerned, with differences in phthalate exposure, risk perceptions, and interest in a natural and healthy diet. This study shows that even those consumers who express strong interest in natural food and low acceptance of food chemicals, and who try to make respective food choices, are exposed to contaminants such as phthalates.     

The value of a player in n-person games

. The article decomposes the Shapley value into a value matrix which gives the value of every player to every other player in n-person games. Element Φ_ij(v) in the value matrix is positive, zero, or negative, dependent on whether row player i is beneficial, has no impact, or is not beneficial for column player j. The elements in each row and in each column of the value matrix sum up to the Shapley value of the respective player. The value matrix is illustrated by the voting procedure in the European Council of Ministers 1981–1995. Received: 9 September 1998/Accepted: 11 February 2000     

Religion und Bildungserfolg im Migrationskontext – Theoretische Argumente,empirische Befunde und offene Fragen

Religion has received extensive attention as a factor influencing immigrants’ integration. This paper examines the role of religion in explaining ethnic educational inequalities in Germany. Due to a general lack of research in this field, the paper provides an overview of existing empirical findings, specifies theoretical arguments on how religious affiliation, belief and participation possibly affect educational achievement among children of immigrants. Using data from the first wave of the “Children of Immigrants Longitudinal Survey in four European Countries” collected in 2010/11 the paper tests key arguments on the influence of religion on the educational attainment among 14-year-old immigrant and non-immigrant students at German schools. Compared to other religious groups, Muslims display lower rates of educational achievement. However, this can be largely explained by their social background and is independent from their levels of individual religiosity. Interestingly, individual religiosity has a positive effect on the educational achievement among Protestant students, whether with or without a migration background.     

The Viability of Career Maturity Theory: A Developmental—Contextual Perspective

The critical role of the timing of person—context interactions is important in the conceptualization of the school-to-work transition. It is argued that career maturity, with its focus on the individual and its ties to stage models and notions of age-appropriateness, gives insufficient attention to the particular contexts of time and culture within which it may be observed. The use of recent advances in developmental theory is suggested as a viable alternative for understanding developmental transitions. Findings from the research literature and from a recent study of young adults from former East Germany and former West Germany are cited in support of this proposal. These findings highlight limitations of the construct of career maturity in showing how individual differences and contextual factors contribute to the school-to-work transition in contrasting environments of former East and West Germany.     

Frame Correction Modelling with Applications to the German Register‐Assisted Census 2011

Frame corrections have been studied in census applications for a long time. One very promising method is dual system estimation, which is based on capture–recapture models. These methods have been applied recently in the USA, England, Israel and Switzerland. In order to gain information on subgroups of the population, structure preserving estimators can be applied [i.e. structure preserving estimation (SPREE) and generalized SPREE]. The present paper extends the SPREE approach with an alternative distance function, the chi‐square. The new method has shown improved estimates in our application with very small domains. A comparative study based on a large‐scale Monte Carlo simulation elaborates on advantages and disadvantages of the estimators in the context of the German register‐assisted Census 2011.     

Religion und Gesellschaft – Aktuelle Perspektiven

Increasing public attention to religious questions has in the past years re-invigorated the sociology of religion. As an introduction to the present special issue we outline some institutional and intellectual developments of German language sociology of religion since the post-war period. We furthermore highlight five current trends of the subdiscipline that pertain to the concept of religion, to debates over secularization, to methodological questions of sociological explanation, to interdisciplinary research on religions under conditions of globalization, and to the refinement of quantitative as well as qualitative research methods. Having argued that these trends attest to an increasingly global-comparative approach, we conclude with some research perspectives for future sociology of religion.     

Estimation and regularization techniques for regression models with multidimensional prediction functions

Boosting is one of the most important methods for fitting regression models and building prediction rules. A notable feature of boosting is that the technique can be modified such that it includes a built-in mechanism for shrinking coefficient estimates and variable selection. This regularization mechanism makes boosting a suitable method for analyzing data characterized by small sample sizes and large numbers of predictors. We extend the existing methodology by developing a boosting method for prediction functions with multiple components. Such multidimensional functions occur in many types of statistical models, for example in count data models and in models involving outcome variables with a mixture distribution. As will be demonstrated, the new algorithm is suitable for both the estimation of the prediction function and regularization of the estimates. In addition, nuisance parameters can be estimated simultaneously with the prediction function.     

Numerical solution of optimal allocation problems in stratified sampling under box constraints

Modern sampling designs in survey statistics, in general, are constructed in order to optimize the accuracy of estimators such as totals, means and proportions. In stratified random sampling a variance minimal solution was introduced by Neyman and Tschuprov. However, practical constraints may lead to limitations of the domain of sampling fractions which have to be considered within the optimization process. Special attention on the complexity of numerical solutions has to be paid in cases with many strata or when the optimal allocation has to be applied repeatedly, such as in iterative solutions of stratification problems. The present article gives an overview of recent numerical algorithms which allow adequate inclusion of box constraints in the numerical optimization process. These box constraints may play an important role in statistical modeling. Furthermore, a new approach through a fixed point iteration with a finite termination property is presented.