Variability and Uncertainty in Swedish Exposure Factors for Use in Quantitative Exposure Assessments

Information of exposure factors used in quantitative risk assessments has previously been compiled and reported for U.S. and European populations. However, due to the advancement of science and knowledge, these reports are in continuous need of updating with new data. Equally important is the change over time of many exposure factors related to both physiological characteristics and human behavior. Body weight, skin surface, time use, and dietary habits are some of the most obvious examples covered here. A wealth of data is available from literature not primarily gathered for the purpose of risk assessment. Here we review a number of key exposure factors and compare these factors between northern Europe—here represented by Sweden—and the United States. Many previous compilations of exposure factor data focus on interindividual variability and variability between sexes and age groups, while uncertainty is mainly dealt with in a qualitative way. In this article variability is assessed along with uncertainty. As estimates of central tendency and interindividual variability, mean, standard deviation, skewness, kurtosis, and multiple percentiles were calculated, while uncertainty was characterized using 95% confidence intervals for these parameters. The presented statistics are appropriate for use in deterministic analyses using point estimates for each input parameter as well as in probabilistic assessments.     

New Results on the Small-Sample Properties of Some Robust Univariate Estimators of Location

This article compares eight estimators in terms of relative efficiencies with the univariate mean, some of which have not been compared previously. Four estimators, when testing hypotheses, are compared in terms of actual Type I errors. In terms of point estimation, the modified one-step M-estimator, one-step M-estimator, and rfch estimator are found to be the three best choices depending on the proportion of outliers. In terms of actual Type I errors, the modified one-step M estimator's and rfch estimator's level was between.045 and.055 in 5 out of 7 situations when real data were used in simulations.     

A generalized,multi-stage adjusted,latent class linear mixed model for testing genetic association

ABSTRACT

In this study, a Generalized, Multi-Stage Adjusted, Latent Class Linear Mixed Model is proposed for modeling the heterogeneous distributed phenotype and genetic information across the whole genome in the presence of both serial and familial correlations. Genome data were analyzed by applying the proposed model to Genetic Analysis Workshop (GAW) data, and the model results were compared to the results of standard models. Moreover, the potential of the model is discussed compared to simulated data. As a result of model comparisons, the information criteria and the genomic control parameter were found to be smaller. The results of a power analysis show that the proposed model is more powerful.     

The Restricted and Unrestricted Two-Parameter Estimators

In this article, we introduce a new two-parameter estimator by grafting the contraction estimator into the modified ridge estimator proposed by Swindel (1976 Swindel , B. F. ( 1976 ). Good ridge estimators based on prior information . Commun. Statist. Theor. Meth. A5 : 1065 – 1075 .[Taylor & Francis Online], [Web of Science ®] , [Google Scholar]). This new two-parameter estimator is a general estimator which includes the ordinary least squares, the ridge, the Liu, and the contraction estimators as special cases. Furthermore, by setting restrictions Rβ = r on the parameter values we introduce a new restricted two-parameter estimator which includes the well-known restricted least squares, the restricted ridge proposed by Groß (2003 Groß , J. ( 2003 ). Restricted ridge estimation . Statist. Probab. Lett. 65 : 57 – 64 .[Crossref], [Web of Science ®] , [Google Scholar]), the restricted contraction estimators, and a new restricted Liu estimator which we call the modified restricted Liu estimator different from the restricted Liu estimator proposed by Kaç?ranlar et al. (1999 Kaç?ranlar , S. , Sakall?o?lu , S. , Akdeniz , F. , Styan , G. P. H. , Werner , H. J. ( 1999 ). A new biased estimator in linear regression and a detailed analysis of the widely-analysed dataset on Portland cement . Sankhya Ser. B., Ind. J. Statist. 61 : 443 – 459 . [Google Scholar]). We also obtain necessary and sufficient condition for the superiority of the new two-parameter estimator over the ordinary least squares estimator and the comparison of the new restricted two-parameter estimator to the new two-parameter estimator is done by the criterion of matrix mean square error. The estimators of the biasing parameters are given and a simulation study is done for the comparison as well as the determination of the biasing parameters.     

Nash implementation via hyperfunctions

Hyperfunctions are social choice rules which assign sets of alternatives to preference profiles over sets. Therefore, they are more general objects compared to standard (social choice) correspondences. In fact, every correspondence can be expressed in terms of an equivalent hyperfunction. We give a partial characterization of Nash-implementable hyperfunctions and explore the conditions under which correspondences have Nash-implementable equivalent hyperfunctions. While the strength of these conditions depends on the axioms used to extend preferences over alternatives to sets, they are at most as strong as the conjunction of Maskin monotonicity with the no veto power condition. Thus, our approach expands the set of Nash-implementable social choice rules. In fact, social choice rules such as the majority rule and the top cycle are Nash-implementable through their equivalent hyperfunctions, while they are not Maskin-monotonic, and thus, not Nash-implementable in the standard framework.

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Betriebsinterne Arbeitsmärkte, Hierarchien und Neueinstellungen: Eine empirische Untersuchung mit Personaldaten

Many empirical studies which deal with internal labour markets are related to the work of Doeringer and Piore (1971). The majority of these studies cannot find closed internal labour markets with entry positions at the lower end of a firm’s hierarchy. Most of these studies, however, use data from financial and service industries, managerial or other white-collar workers. Doeringer and Piore (1971) state that closed internal labour markets with clearly defined entry positions should be found especially for blue-collar workers in the manufacturing industry, because firm specific human capital is of large importance in these industries. In this paper, a large data set of a manufacturing company with blue-collar and white-collar workers is used. We show that the internal labour market of blue-collar workers is more closed than that of white-collar workers. Moreover, we find that firm specific human capital plays a major role in determining the hierarchical position of blue-collar workers. Entries of white-collar workers, however, appear at all hierarchical positions. Furthermore, formal education plays a major role in allocating the white-collar workers.     

The Almon two parameter estimator for the distributed lag models

The two parameter estimator proposed by Özkale and Kaç?ranlar [The restricted and unrestricted two parameter estimators. Comm Statist Theory Methods. 2007;36(15):2707–2725] is a general estimator which includes the ordinary least squares, the ridge and the Liu estimators as special cases. In the present paper we introduce Almon two parameter estimator based on the two parameter estimation procedure to deal with the problem of multicollinearity for the distiributed lag models. This estimator outperforms the Almon estimator according to the matrix mean square error criterion. Moreover, a numerical example and a Monte Carlo simulation experiment are presented by using different estimators of the biasing parameters.     

Uniform trade rules for uncleared markets

We analyze markets in which the price of a traded commodity is such that the supply and the demand are unequal. Under standard assumptions, the agents then have single peaked preferences on their consumption or production choices. For such markets, we propose a class of Uniform trade rules each of which determines the volume of trade as the median of total demand, total supply, and an exogenous constant. Then these rules allocate this volume “uniformly” on either side of the market. We evaluate these “trade rules” on the basis of some standard axioms in the literature. We show that they uniquely satisfy Pareto optimality, strategy proofness, no-envy, and an informational simplicity axiom that we introduce. We also analyze the implications of anonymity, renegotiation proofness, and voluntary trade on this domain.