A property of coefficients of variation for ordered bivariate log-normal variables

This paper considers the maximum and minimum of a pair of log-normal variables with equal mean. It shows that either order statistic has a smaller coefficient of variation than the two original log-normal variables provided the latter are of equal variance. When the variances are unequal, as the variance ratio increases, the minimum (maximum), has a smaller coefficient of variation if the correlation coefficient of the log-normal variables is small (small) and the variances are large (small).     

A Diamond-Stiglitz approach to the demand for self-protection

The existing research concerning the relationship between risk aversion and prudence and the demand for self-protection assumes that the loss variable follows a Bernoulli distribution, and that changes in the level of self-protection are mean preserving. The analysis here replaces these two very strong conditions with ones which are more general. When doing this, the method of analysis is also significantly modified. This modification includes representing a change in the level of self-protection using the procedure developed by Diamond and Stiglitz (Journal of Economic Theory 8:337-360, 1974) for representing a change in risk. This alternate representation allows the existing findings to be generalized considerably, and also simplifies the analysis.     

Relationship of interpersonal behaviors and health-related control appraisals to patient satisfaction and compliance in a university health center

OBJECTIVE: The authors' aim was to evaluate patient-provider relationships in a college health center. PARTICIPANTS: Eighty student patients and their health-care providers. METHODS: Patients completed a measure of perceived health competence before a consultation and measures of provider participatory behavior and interpersonal behavior before and after the consultation. They evaluated their satisfaction with care and compliance after the consultation and again 2 weeks later. Providers completed measures of their participatory behavior and patients' interpersonal behavior after the consultation. RESULTS: Patients preferred to be well informed and to have their preferences taken into account, and generally felt competent at managing their own health affairs. They indicated they obtained the high level of participation they desired. Patients desired and actually experienced friendly and submissive providers. Degree of match between patients' desired and actual level of involvement in their care was associated with greater satisfaction. A greater match between the extent to which they desired the provider to be affiliative and the provider's actual affiliative behavior was associated with more satisfaction. No variables were predictive of patient compliance. CONCLUSION: The authors discuss results in terms of the influence of situational factors characteristic of a college health center.     

The self-perceptions and interpersonal relationships of persons with significant physical disabilities: a qualitative pilot study

This exploratory, qualitative research was conducted to obtain the perspectives of people with significant physical disabilities regarding factors that have facilitated and hindered the development of a positive self-concept, participation in the broader society, and the formation of interpersonal relationships. The sample was high achieving in terms of education and/or career and attributed positive self-perceptions and their success in the broader society and interpersonal relationships to the attitudes and perceptions regarding their abilities, talents, and potential modeled in supportive family relationships. Females reported the influence of significant others most often, and males the effectiveness of their personality characteristics. Societal barriers, both practical and attitudinal, were reported along with the process for developing a positive selfperception despite these.     

A Stochastic Goal Program for Employee Scheduling*

Deterministic goal programs for employee scheduling decisions attempt to minimize expected operating costs by assigning the ideal number of employees to each feasible schedule. For each period in the planning horizon, managers must first determine the amount of labor that should be scheduled for duty. These requirements are often established with marginal analysis techniques, which use estimates for incremental labor costs and shortage expenses. Typically, each period in the planning horizon is evaluated as an independent epoch. An implicit assumption is that individual employees can be assigned to schedules with as little as a single period of work. If this assumption violates local work rules, the labor requirements parameters for the deterministic goal program may be suboptimal. As we show in this research, this well-known limitation can lead to costly staffing and scheduling errors. We propose an employee scheduling model that overcomes this limitation by integrating the labor requirements and scheduling decisions. Instead of a single, externally determined staffing goal for each period, the model uses a probability distribution for the quantity of labor required. The model is free to choose an appropriate staffing level for each period, eliminating the need for a separate goal-setting procedure. In most cases this results in better, less costly decisions. In addition, the proposed model easily accommodates both linear and nonlinear under- and overstaffing penalties. We use simple examples to demonstrate many of these advantages and to illustrate the key techniques necessary to implement our model. We also assess its performance in a study of more than 1,700 simulated stochastic employee scheduling problems.     

The U.S. Health System and Immigration: An Institutional Interpretation1

We examine the institutions that comprise the U.S. health system and their relationship to a surging immigrant population. The clash between the system and this human flow originates in the large number of immigrants who are unauthorized, poor, and uninsured and, hence, unable to access a system largely based on ability to pay. Basic concepts from sociological theory are brought to bear on the analysis of this clash and its consequences. Data from a recently completed study of health institutions in three areas of the United States are used as an empirical basis to illustrate various aspects of this complex relation. Implications of our results for theory and future health policy are discussed.     

Some indications of limits to framing the policy preferences of the civically engaged: Interplay of social capital,race attitudes,and social justice frames

Our experiment, which tested support for a hypothetical social welfare program, found that the civically engaged as a whole were resistant to social justice framing employing universalistic versus particularistic standards. We suggest the lack of a framing effect was due to the use of a preexisting, shared “symbolic racism” frame. Social justice framing did succeed for those whose attitudes toward symbolic racism were ambivalent or neutral. Other factors including sex, income level, political participation, and ideology significantly influenced choice. These results provide some indications of limits to experimental framing of policy preferences of the civically engaged in their institutional settings.     

MARKET STRUCTURE AND MEDIA DIVERSITY

We estimate a mixed logit model of the demand for local news service. Results provide evidence that suggest the representative consumer values more diverse news, more coverage of multicultural issues, and more information on community news, and has a distaste for advertising. Demand estimates are used to calculate the impact on consumer welfare from a marginal decrease in the number of independent television stations that lowers the amount of diversity, multiculturalism, community news, and advertising. Consumer welfare decreases, but the losses are smaller in large markets. For example, small‐market consumers lose $45 million annually while large‐market consumers lose $13 million. (JEL C9, C25, L13, L82, L96)     

A Bayesian sequential design with binary outcome

Several researchers have proposed solutions to control type I error rate in sequential designs. The use of Bayesian sequential design becomes more common; however, these designs are subject to inflation of the type I error rate. We propose a Bayesian sequential design for binary outcome using an alpha‐spending function to control the overall type I error rate. Algorithms are presented for calculating critical values and power for the proposed designs. We also propose a new stopping rule for futility. Sensitivity analysis is implemented for assessing the effects of varying the parameters of the prior distribution and maximum total sample size on critical values. Alpha‐spending functions are compared using power and actual sample size through simulations. Further simulations show that, when total sample size is fixed, the proposed design has greater power than the traditional Bayesian sequential design, which sets equal stopping bounds at all interim analyses. We also find that the proposed design with the new stopping for futility rule results in greater power and can stop earlier with a smaller actual sample size, compared with the traditional stopping rule for futility when all other conditions are held constant. Finally, we apply the proposed method to a real data set and compare the results with traditional designs.