An Evaluation of Stimulus Preference Assessment Methodology in Organizational Behavior Management

The organizational behavior management literature has yielded few stimulus preference assessment methodologies for use with employees. The current investigation compared three preference assessments (ranking, survey, and multiple stimulus without replacement procedures) found in the organizational behavior management literature for their ability to predict reinforcers for direct care staff members’ behavior. In the first experiment all assessments were effective for predicting reinforcers, but the results were limited by a lack of control items in the assessment. In the second experiment the survey and ranking assessments both proved to be effective for identifying reinforcers and neutral or ineffective stimuli. Implications of these results and directions for future research are discussed.     

Benchmark Dose Analysis via Nonparametric Regression Modeling

Estimation of benchmark doses (BMDs) in quantitative risk assessment traditionally is based upon parametric dose‐response modeling. It is a well‐known concern, however, that if the chosen parametric model is uncertain and/or misspecified, inaccurate and possibly unsafe low‐dose inferences can result. We describe a nonparametric approach for estimating BMDs with quantal‐response data based on an isotonic regression method, and also study use of corresponding, nonparametric, bootstrap‐based confidence limits for the BMD. We explore the confidence limits’ small‐sample properties via a simulation study, and illustrate the calculations with an example from cancer risk assessment. It is seen that this nonparametric approach can provide a useful alternative for BMD estimation when faced with the problem of parametric model uncertainty.     

Naming,Defining, and Classifying the Condition (Formerly?) Known as Mental Retardation

Abstract

Key controversies and diverse perspectives are summarized regarding terminology, definition, and classification issues in the field of mental retardation. Six questions are provided to guide consideration of critical issues. Conclusions are drawn and implications for professional practice are discussed.     

An Empirical Approach to Sufficient Similarity: Combining Exposure Data and Mixtures Toxicology Data

When assessing risks posed by environmental chemical mixtures, whole mixture approaches are preferred to component approaches. When toxicological data on whole mixtures as they occur in the environment are not available, Environmental Protection Agency guidance states that toxicity data from a mixture considered “sufficiently similar” to the environmental mixture can serve as a surrogate. We propose a novel method to examine whether mixtures are sufficiently similar, when exposure data and mixture toxicity study data from at least one representative mixture are available. We define sufficient similarity using equivalence testing methodology comparing the distance between benchmark dose estimates for mixtures in both data‐rich and data‐poor cases. We construct a “similar mixtures risk indicator”(SMRI) (analogous to the hazard index) on sufficiently similar mixtures linking exposure data with mixtures toxicology data. The methods are illustrated using pyrethroid mixtures occurrence data collected in child care centers (CCC) and dose‐response data examining acute neurobehavioral effects of pyrethroid mixtures in rats. Our method shows that the mixtures from 90% of the CCCs were sufficiently similar to the dose‐response study mixture. Using exposure estimates for a hypothetical child, the 95th percentile of the (weighted) SMRI for these sufficiently similar mixtures was 0.20 (i.e., where SMRI <1, less concern; >1, more concern).     

On Signatures of Series and Parallel Systems Consisting of Modules with Arbitrary Structures

The signature of a system is a useful concept not only in the analysis of binary coherent systems but also in network reliability. Computation of system signature is a well-defined combinatorial problem. This article is concerned with the computation of signature vectors of series and parallel systems consisting of modules. We derive simple formulas for the signature and minimal signature of series and parallel systems based on signatures and minimal signatures of modules with given structures. We present computational results to illustrate the findings.     

Selective Maintenance in System Reliability with Random Costs of Repairing and Replacing the Components

In this paper we consider the problem of determining the optimum number of repairable and replaceable components to maximize a system's reliability when both, the cost of repairing the components and the cost of replacement of components by new ones, are random. We formulate it as a problem of non-linear stochastic programming. The solution is obtained through Chance Constrained programming. We also consider the problem of finding the optimal maintenance cost for a given reliability requirement of the system. The solution is then obtained by using Modified E-model. A numerical example is solved for both the formulations.     

Exploring the Use of the Stages of Change Model to Increase Organ Donations Among African Americans

Abstract

The success of organ transplants is affected by the degree of antigen match between donor and recipient. With organ transplants among African Americans, finding a good antigen match is difficult. While the consent rate for organ donations among Caucasians is 50%, this rate among African Americans is only 12%. The resulting ratio of donors to “recipients” is 1 to 9 in African Americans. The majority of organs received by African Americans come from Caucasian donors, thereby reducing the probability of an antigen match and increasing the probability of organ rejection. These circumstances could be improved if the organ donation rate eamong African Americans was increased. There is some empirical support for the theory that behavior change occurs through identifiable stages. This paper presents evidence for the construct validity of a stage of change measure suitable for use in designing and evaluating attempts to promote organ donations in the African American community. Use of this measure also permits clinicians to assess how receptive a client will be to organ donation promotional material. Use of this measure offers the possibility of refining approaches to organ donations among African Americans. Increases in the donor rate will result in a larger pool of antigen compatible organs in this subpopulation.     

Order statistics from the linear-exponential distribution,part I: increasing hazard rate case

For the linear-exponential distribution with increasing hazard rate, exact and explicit expressions for means, product moments and percentage points of order statistics are obtained. Some recurrence relations for both single and product moments of order statistics are also derived. These recurrence relations would enable one to obtain all the higher order moments of order statistics for all sample sizes from those of the lower order     

Water Adherence Factors for Human Skin

On incidental dermal exposure to chemicals in water, a key exposure factor is the amount of water adhering to skin. Although soil adherence factors have been developed for risk assessment, measurements of water adherence on human skin have not been described. In the Environmental Protection Agency's (EPA's) dermal risk assessment guidance, dermal dose from environmental exposures is based upon the flux rate across the skin, which assumes that an unlimited amount of chemical is available for absorption. This assumption is applicable to certain exposure scenarios such as swimming and bathing. However, exposures to contaminated water frequently involve scenarios where the available chemical is limited by the amount of water adhering to the skin, for example, during accidental splashes. We conducted studies in human volunteers to investigate water adherence per unit area of skin after brief contact with water. In two sets of experiments, either water was applied with a micropipette to 10‐cm² areas of the lower leg, foot, and hand, or the foot and hand were briefly immersed in water. In males, using a micropipette, water adherence ranged from 1.93 (foot) to 7.13 μL/cm² (lower leg). In females, it ranged from 1.10 (lower leg) to 4.83 μL/cm² (hand). Hand and foot immersion resulted in relatively higher values of 6.89 and 5.17 μL/cm², respectively, in males, and 5.40 and 6.39 μL/cm² in females. Water adherence was affected by amount of body hair and type of exposure. Water adherence factors can be used to calculate the applied dose per unit area for exposures involving intermittent water contact.     

Weighted Stochastic Restricted Estimation in Linear Measurement Error Models

This article discusses the consistent estimation of the parameters in a linear measurement error model when stochastic linear restrictions on regression coefficients are available. We propose some methodologies to obtain the consistent estimation when either the covariance matrix of the measurement errors or the reliability matrix of independent variables is known. Their finite- and large-sample properties are derived with not necessarily normal errors. A Monte Carlo simulation is carried out to study the the finite properties of the estimators.