Union wages, rents, and skills in health care labor markets

We examine the effect of unions on the earnings of health care workers, with emphasis on the measurement and sources of union wage premiums. Using data constructed from the 1973 though 1994 Current Population Surveys, standard union premium estimates are found to be substantially lower among workers in health care than in other sectors of the economy, and to be smaller among higher skill than among lower skill occupational groups. Longitudinal analysis of workers switching union status, which controls for worker-specific skills, indicates a small impact of unions on earnings within both high and low skilled health care occupations. Evidence is found for small, but significant, union threat effects in health care labor markets. It has been argued that recent legal changes in bargaining unit determination should enhance union organizing and bargaining power. Although we cannot rule this out, such effects are not readily apparent in our data. The authors appreciate the assistance of David Macpherson, who helped develop the CPS data files used in the paper.     

Discretionary Use of Involuntary Commitment by Case Managers of Mental Health Clients: A Case Study of Divergent Views

In an exploratory study, case managers held divergent views about their appropriate roles in involuntarily committing clients to psychiatric care. In light of vague organizational guidelines about appropriate use of involuntary commitment, case managers drew on professional social work values to form views about commitment. These values supported client self-determination, but did not clearly delineate ways for case managers' use of power and discretion concerning involuntary hospitalization, resulting in a range of understandings among case managers. This article provides a history of discretionary choices in the helping professions, cases illustrating divergent views about commitment among case managers and consequences for clients, and a discussion of ways this range may be narrowed in the future.     

Predicting random effects with an expanded finite population mixed model

Prediction of random effects is an important problem with expanding applications. In the simplest context, the problem corresponds to prediction of the latent value (the mean) of a realized cluster selected via two-stage sampling. Recently, Stanek and Singer [Predicting random effects from finite population clustered samples with response error. J. Amer. Statist. Assoc. 99, 119–130] developed best linear unbiased predictors (BLUP) under a finite population mixed model that outperform BLUPs from mixed models and superpopulation models. Their setup, however, does not allow for unequally sized clusters. To overcome this drawback, we consider an expanded finite population mixed model based on a larger set of random variables that span a higher dimensional space than those typically applied to such problems. We show that BLUPs for linear combinations of the realized cluster means derived under such a model have considerably smaller mean squared error (MSE) than those obtained from mixed models, superpopulation models, and finite population mixed models. We motivate our general approach by an example developed for two-stage cluster sampling and show that it faithfully captures the stochastic aspects of sampling in the problem. We also consider simulation studies to illustrate the increased accuracy of the BLUP obtained under the expanded finite population mixed model.     

Relationship marketing: Its key role in entrepreneurship

The authors argue that relationship marketing can readily be adopted by a small entrepreneurial business but it will need to be adapted to the entrepreneurial environment into which it is introduced. Results from initial research suggest that entrepreneurial enterprises employ relationship marketing more effectively than less entrepreneurial organisations and they derive commercial benefits such as higher growth rates and fewer customer defections. The authors argue that entrepreneurship can be learned and so less entrepreneurial firms have the potential to learn from more successful entrepreneurs. They offer some specific recommendations but they recognise that the task is not easy because the SME has to create an internal culture that is capable of both embracing relationship marketing and being alert to opportunity.     

MODEL SELECTION CRITERIA FOR LOGLINEAR MODELS

Considerable work has been devoted to developing model selection criteria for normal theory regression models. Less attention has been paid to discrete data. We develop two loglinear model selection criteria for Poisson counts. These criteria are based on an estimated bias adjustment of the Akaike information criterion. We observe in a simulation study that the corrected statistics provide good model choices and relatively accurate estimates of the mean structure.     

Empirical Bayes vs. fully Bayes variable selection

For the problem of variable selection for the normal linear model, fixed penalty selection criteria such as AIC, _Cp${\mathrm{C}}_p$, BIC and RIC correspond to the posterior modes of a hierarchical Bayes model for various fixed hyperparameter settings. Adaptive selection criteria obtained by empirical Bayes estimation of the hyperparameters have been shown by George and Foster [2000. Calibration and Empirical Bayes variable selection. Biometrika 87(4), 731–747] to improve on these fixed selection criteria. In this paper, we study the potential of alternative fully Bayes methods, which instead margin out the hyperparameters with respect to prior distributions. Several structured prior formulations are considered for which fully Bayes selection and estimation methods are obtained. Analytical and simulation comparisons with empirical Bayes counterparts are studied.     

Palliative healthcare: cost reduction and quality enhancement using end-of-life survey methodology

American medical institutions throughout the 20th century prescribed high customer satisfaction, but when it came to death, largely ignored it. An accelerated accumulation of esoteric medical information and the application of this knowledge to affect new cures and longer lives instilled an unquestioning reverence for the medical community among the patient population. Diminishing marginal gains in life expectancy, escalating costs related to life sustaining technologies, and a psychographic shift in the dominant consumer base have challenged this traditional reverence. Armed with unprecedented access to medical information, a more knowledgeable and assertive patient population has emerged in the 21st century to institute its own standards of what constitutes quality health care. In terms of end of life care, this has meant recognition that the emotional needs of the dying have been largely underserved by the current American medical model. Patients and their families are no longer willing to accept the traditional medical perspective of death as failure and have numerous international palliative care models that serve as benchmarks of success when it comes to quality of dying. When cure is a possibility, Americans will pursue it at all costs, but when it is not a possibility, they want honest communication and the opportunity to say good-bye to their loved ones. In the context of these emergent needs, life review is offered as a solution. The value proposition targets not only dying patients and their families, but also society as a whole.