Sampling Strategies for Toxic Air Contaminants

Annual concentrations of toxic air contaminants are of primary concern from the perspective of chronic human exposure assessment and risk analysis. Despite recent advances in air quality monitoring technology, resource and technical constraints often impose limitations on the availability of a sufficient number of ambient concentration measurements for performing environmental risk analysis. Therefore, sample size limitations, representativeness of data, and uncertainties in the estimated annual mean concentration must be examined before performing quantitative risk analysis. In this paper, we discuss several factors that need to be considered in designing field-sampling programs for toxic air contaminants and in verifying compliance with environmental regulations. Specifically, we examine the behavior of SO2, TSP, and CO data as surrogates for toxic air contaminants and as examples of point source, area source, and line source-dominated pollutants, respectively, from the standpoint of sampling design. We demonstrate the use of bootstrap resampling method and normal theory in estimating the annual mean concentration and its 95% confidence bounds from limited sampling data, and illustrate the application of operating characteristic (OC) curves to determine optimum sample size and other sampling strategies. We also outline a statistical procedure, based on a one-sided t-test, that utilizes the sampled concentration data for evaluating whether a sampling site is compliance with relevant ambient guideline concentrations for toxic air contaminants.     

Coaching für Führungskräfte im Krankenhaus Baustein einer Strategie zum Total Quality Management

Coaching of managers in hospitals as component of a total quality management strategy The author delineates the changed conditions of hospitals at the beginning of the new millenium. In order to be up to date with the growing challenges and the need for change a Total Quality Management (TQM) is necessary. This TQM sees the satisfaction of clients and of employees as crucial for all reorganization processes. The realization in everyday hospital life requires a total personnel development concept, with special regard to the managers and their specific needs for support by supervisors resp. coaches.     

Minority Poverty in Nonmetropolitan Texas*

Abstract Despite a high prevalence of poverty among minorities in nonmetropolitan areas, research and policy concerns regarding poverty have continued focusing on metropolitan minorities. This study uses a model integrating individual, household, and structural factors to examine poverty among Latinos, blacks, and Anglos in nonmetropolitan and, for comparative purposes, metropolitan areas, using data from the 1985 Special Texas Census TDHS 1987. The findings show that minorities in nonmetropolitan areas tend to have the highest poverty rates. In addition, consistent as well as divergent patterns exist among the six ethnic-resident groups with respect to the relationships among the various individual, household, and structural factors and poverty.     

Local polynomial estimation of Poisson intensities in the presence of reporting delays

Summary.  The system for monitoring suicides in Hong Kong has considerable delays in reporting as the cause of death needs to be determined by a coroner's investigation. However, timely estimates of suicide rates are desirable to assist in the formulation of public health policies. This motivated us to develop a non-parametric procedure to estimate the intensity function of a Poisson process in the presence of reporting delays. We give closed form estimators of the Poisson intensity and the delay distribution, conduct simulation studies to evaluate the method proposed and derive their asymptotic properties. The method proposed is applied to estimate the intensity of suicide in Hong Kong.     

Data skeletons: simultaneous estimation of multiple quantiles for massive streaming datasets with applications to density estimation

We consider the problem of density estimation when the data is in the form of a continuous stream with no fixed length. In this setting, implementations of the usual methods of density estimation such as kernel density estimation are problematic. We propose a method of density estimation for massive datasets that is based upon taking the derivative of a smooth curve that has been fit through a set of quantile estimates. To achieve this, a low-storage, single-pass, sequential method is proposed for simultaneous estimation of multiple quantiles for massive datasets that form the basis of this method of density estimation. For comparison, we also consider a sequential kernel density estimator. The proposed methods are shown through simulation study to perform well and to have several distinct advantages over existing methods.     

Constrained allocation problems with single-peaked preferences: An axiomatic analysis

We introduce a new class of problems that contains two existing classes: allocation problems with single-peaked preferences and bankruptcy problems. On this class, we analyze the implications of well-known properties such as Pareto optimality, strategy-proofness, resource-monotonicity, no-envy, equal treatment of equals, and two new properties we introduce, hierarchical no-envy and independence of nonbinding constraints. Unlike earlier literature, we consider rules that allow free-disposability. We present characterizations of a rule we introduce on this domain. We relate this rule to well-known rules on the aforementioned subdomains. Based on this relation, we present a characterization of a well-known bankruptcy rule called the constrained equal awards rule. Received: 22 June 2000/Accepted: 21 March 2002 This paper is based on the first chapter of my Ph.D. thesis submitted to the University of Rochester. I wish to thank my advisor, William Thomson, for helpful comments and suggestions.     

Organizational Compatibility and Workplace Drug Testing: Modeling the Adoption of Innovative Social Control Practices

Few researchers have examined organizational variation in the adoption of workplace drug testing, but innovation theory suggests that adoption is more likely when it is compatible with an organization's values, previously introduced ideas, and needs. Using data from the 1997 National Employee Survey, this research models the effects of organizational compatibility, industry, and establishment size on the adoption of drug testing. The data reveal that compatibility, as measured by an organization's rules orientation, presence of an employee assistance program, and mechanization, is associated with the adoption of drug testing. As predicted, the adoption of drug testing varies across industries and by establishment size.     

Land Ownership as a Determinant of Temporary Migration in Nang Rong, Thailand

In this study I consider landownership as a determinant of temporary migrationin a rural area of Thailand. Previous researchon rural areas in developing countries hasfocused on the use of migration to diversifyhousehold incomes across economic sectors andacross geographic areas. I combine thisliterature with economic theories of migrationto understand the effect of land ownership ontemporary migration of household members inNang Rong, Thailand. I estimate regressionmodels predicting the probability of ahousehold having any temporary migrants, andpredicting the number of male or femaletemporary migrants in the household. I findthat households with smaller landholdings arediversifying through migration in order tosupplement rural income, while households withlarger landholdings are diversifying in orderto overcome the absence of accessible credit inthe village.     

Performance measurement and classification data in DEA: Input-oriented model

This paper presents an improved efficiency measurement tool by modifying the existing data envelopment analysis methodology to permit the incorporation of expert knowledge. A previous paper examined the inclusion of such knowledge within the additive model. This information appeared in the form of a binary classification of a subset of the decision making units under study (e.g. good versus poor performers). In the current paper, we extend this logic to the input-oriented radial projection model. We demonstrate that the inclusion of this and other forms of expert judgment can improve the performance of the DEA tool in the sense that the efficiency scores are more in line with expert/management beliefs.