Global Robustness with Respect to the Loss Function and the Prior

We propose a class [I,S] of loss functions for modeling the imprecise preferences of the decision maker in Bayesian Decision Theory. This class is built upon two extreme loss functions I and S which reflect the limited information about the loss function. We give an approximation of the set of Bayes actions for every loss function in [I,S] and every prior in a mixture class; if the decision space is a subset of , we obtain the exact set.     

The production of criminological experiments

This article examines the production of crime and justice field experiments during the 1990s. Data were collected on the characteristics of criminological experiments funded by the National Institute of Justice (NIJ), the principal research agency of the U.S. Department of Justice, during the 10-year period from 1991 through 2000. The analyses find that, whereas the funds available for research and evaluation at the NIJ increased during this period, the number of projects and the amount of funds awarded supporting field experiments declined. The article describes the characteristics of the experiments funded and assesses the extent to which the reduced support can be attributed to the characteristics of NIJ research funding, research topics, researchers, or criminal justice operational agencies.     

Social Work in Health Care: A Guide to Professional Practice

Abstract

This article describes the evolution of a research program across 18 PhD dissertations over a period of eleven years. Included in this paper is a discussion of the advantages and disadvantages of student and field participation in thematic experimental research. The essential steps in the development of a set of related dissertations also are described. The guidelines for constructing the true experiment as dissertation are outlined. Attention is paid to the resources required to carry out thematic research and the specific ways in which such dissertations have been funded. Characteristics of those students who can best avoid such an approach to a dissertation are examined. Finally the author looks at the product of these dissertations and dissertators in terms of contribution to knowledge, the creation of practitioner manuals for practice interventions, the formation of practice-research faculty, research productivity of these faculty, and the development of the dissertator's clinical skills.     

Reporting cumulative proportion of subjects with an adverse event based on data from multiple studies

Experience has shown us that when data are pooled from multiple studies to create an integrated summary, an analysis based on naïvely‐pooled data is vulnerable to the mischief of Simpson's Paradox. Using the proportions of patients with a target adverse event (AE) as an example, we demonstrate the Paradox's effect on both the comparison and the estimation of the proportions. While meta analytic approaches have been recommended and increasingly used for comparing safety data between treatments, reporting proportions of subjects experiencing a target AE based on data from multiple studies has received little attention. In this paper, we suggest two possible approaches to report these cumulative proportions. In addition, we urge that regulatory guidelines on reporting such proportions be established so that risks can be communicated in a scientifically defensible and balanced manner. Copyright © 2010 John Wiley & Sons, Ltd.     

Seasonal Time Series and Transfer Function Modeling

A simple modification is suggested for the construction of transfer function models relating an output variable Y_t to an input variable X_t when the model for X_t contains operators that cancel out. In addition, the evaluation of transfer function models is discussed by comparing the forecasts with the actual observations.     

Dimensionality reduction approach to multivariate prediction

The authors consider dimensionality reduction methods used for prediction, such as reduced rank regression, principal component regression and partial least squares. They show how it is possible to obtain intermediate solutions by estimating simultaneously the latent variables for the predictors and for the responses. They obtain a continuum of solutions that goes from reduced rank regression to principal component regression via maximum likelihood and least squares estimation. Different solutions are compared using simulated and real data.     

The United States Economic Crisis: Young Adults’ Reports of Economic Pressures, Financial and Religious Coping and Psychological Well-Being

Using a sample of 222 young adults attending college, the present study examined the relative contribution of young adults’ perceived economic pressures, financial coping and religious meaning-making coping strategies in accounting for variation in their reports of psychological well-being within the context of the United States economic crisis. Results suggest a direct relationship between perceived economic pressure and psychological well-being such that young adults who reported having to make more economic adjustments as a result of economic crisis also reported higher levels of depressed mood and anxiety. Young men and women who reported having to make fewer economic adjustments and being able to meet their material needs reported higher levels of life satisfaction. Regardless of young adults’ self-reported level of economic pressures, the use of education and communication financial coping strategies was related to lower levels of self-reported anxiety and depressed mood and greater life satisfaction. Viewing the financial crisis as a punishment from God was generally associated with young adults’ reports of greater depressed mood and less life satisfaction. Implication of findings for research and practice are discussed.     

Multiplicative-interaction logit models for i×j×2 three-way tables

Multiplicative-interaction (M-I) logit models are proposed for three-way IxJx2 contingency tables where the third variable constitutes a binary response. Models are derived by assigning unknown scores to the categories and forming product interactions from them. Asymptotic results under special sampling constraints are derived for maximum likelihood estimates and the goodness-of-fit statistics. The class of models proposed in this paper are found to be useful when no obvious scores are available. An example is included.     

A time series model with random coefficients

There are many time series applications where an experi­menter observes the simultaneous responses of several sub­systems over time. In these instances one is often not interested in the parameters of individual subsystems, but rather in an overall characterization of the system in question. Under the assumption that subsystems are independent and first order autoregressive, the present paper presents two methods for estimating the distribution of the subsystem coefficients.