A Cost–Benefit Analysis of a Family Systems Intervention for Managing Pediatric Chronic Illness

Despite recent increases of psychosocial programs for pediatric chronic illness, few studies have explored their economic benefits. This study investigated the costs–benefits of a family systems‐based, psychosocial intervention for pediatric chronic illness (MEND: Mastering Each New Direction). A quasi‐prospective study compared the 12‐month pre–post direct and indirect costs of 20 families. The total cost for program was estimated to $5,320. Families incurred $15,249 less in direct and $15,627 less in indirect costs after MEND. On average, medical expenses reduced by 86% in direct and indirect costs, for a cost–benefit ratio of 0.17. Therefore, for every dollar spent on the program, families and their third payers saved approximately $5.74. Implications for healthcare policy and reimbursements are discussed.     

Speaking Out: Youth Led Research as a Methodology Used with Homeless Youth

Participatory action research is well documented with marginalized groups, but less is known about participatory action research with homeless youth. The use of youth led research as a methodology was examined among a population of homeless youth. Peer researchers (n = 10) reported on their experience utilizing youth led research methodology. Results indicate that youth led research is a promising methodology for use among homeless youth. Participants reported that the approach positively impacted the quality and quantity of data that could be collected from participants. Further, peer researchers reported individual benefits of feeling that participating in the project mattered, that people listened to them and that they had a voice.     

Using a Verbal Analysis of Lady Gaga’s Applause as a Classroom Exercise for Teaching Verbal Behavior

The Analysis of Verbal Behavior - Learning Skinner’s (1957) verbal behavior taxonomy requires extensive study and practice. Thus, novel classroom exercises might serve this goal. The present...     

CASH INFLOWS AND BUBBLES IN ASSET MARKETS WITH CONSTANT FUNDAMENTAL VALUES

Previous experimental research on asset markets has reported that the level of cash available to traders does not affect asset prices when fundamentals follow a time trajectory that is constant over time. This contrasts with other research indicating that greater cash levels increase prices when fundamental values are decreasing over time. We report a new experiment in which we show that greater initial cash levels are indeed associated with higher prices when fundamental values are constant over time. Thus, high cash levels will lead to bubbles, if the cash is introduced before the market opens. Our results reconcile the two previous sets of findings. (JEL C90, D03, G02, G12)     

COST INCREASES DUE TO DEMAND UNCERTAINTY IN MRP LOT SIZING

This paper analyzes the cost increases due to demand uncertainty in single-level MRP lot sizing on a rolling horizon. It is shown that forecast errors have a tremendous effect on the cost effectiveness of lot-sizing techniques even when these forecast errors are small. Moreover, the cost differences between different techniques become rather insignificant in the presence of forecast errors. Since most industrial firms face demand uncertainty to some extent, our findings may have important managerial implications. Various simulation experiments give insight into both the nature and the magnitude of the cost increases for different heuristics. Analytical results are developed for the constant-demand case with random noise and forecasting by exponential smoothing. It is also shown how optimal buffers can be obtained by use of a simple model. Although the analysis in this paper is restricted to simplified cases, the results merit further consideration and study. This paper is one of the first to inject forecast errors into MRP lot-sizing research. As such it attempts to deal with one of the major objections against the practical relevance of previous research in this area.     

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.     

Determinanten des Informationsgehalts von Managementprognosen – eine empirische Untersuchung anhand der DAX und MDAX-Unternehmen

In this article the characteristics and determinants of the information content of management earnings forecasts of the German DAX and MDAX companies between 2002 and 2005 are analyzed. As proxy for the information content I use the precision of the wording of a forecast. I can show that the forecasts of MDAX companies are more precisely formulated than those of DAX companies. Furthermore forecasts are formulated more precisely, when companies have, (1) a lower percentage of intangible assets, (2) lower market capitalization, (3) lower volatility of earnings and (4) a higher need for external financing.