Finite mixture models with concomitant information: assessing diagnostic criteria for diabetes

The World Health Organization (WHO) diagnostic criteria for diabetes mellitus were determined in part by evidence that in some populations the plasma glucose level 2 h after an oral glucose load is a mixture of two distinct distributions. We present a finite mixture model that allows the two component densities to be generalized linear models and the mixture probability to be a logistic regression model. The model allows us to estimate the prevalence of diabetes and sensitivity and specificity of the diagnostic criteria as a function of covariates and to estimate them in the absence of an external standard. Sensitivity is the probability that a test indicates disease conditionally on disease being present. Specificity is the probability that a test indicates no disease conditionally on no disease being present. We obtained maximum likelihood estimates via the EM algorithm and derived the standard errors from the information matrix and by the bootstrap. In the application to data from the diabetes in Egypt project a two-component mixture model fits well and the two components are interpreted as normal and diabetes. The means and variances are similar to results found in other populations. The minimum misclassification cutpoints decrease with age, are lower in urban areas and are higher in rural areas than the 200 mg dl^-1 cutpoint recommended by the WHO. These differences are modest and our results generally support the WHO criterion. Our methods allow the direct inclusion of concomitant data whereas past analyses were based on partitioning the data.     

Ability, disability, and the oldest old

A measure of range of ability is used to profile the 85-years-old-and-older (oldest old) population, including the highly disabled institutional population. This new measure uses two new questions available in the 1990 Decennial Census concerning a self-care limitation and a mobility limitation as well as the usual question concerning a work limitation. In addition to examining the extent of disability among the oldest old, the article examines the extent of care potentially available in the household as well as the economic characteristics of this age group. It is also profiled in terms of relevant personal characteristics, including age, gender, marital status, race, ethnicity, rural residence, education, and employment. A key question addressed is the need for help or care among the oldest old and how various long-term care proposals would meet such needs. A careful analysis of this unique and growing population is necessary to both allay fears of the cost of care or help as well as to dispel stereotypes of this age group as frail and dependent, and in need of institutional care.     

Planning for productivity

In the 1980s the subject of productivity will receive increasing attention as the old macro economic policies are replaced by micro economic policies. Everyone in various ways will discover the changes which will be involved in learning the real economic facts of life. The need to improve productivity and business performance is urgent and yet it is an area which is being neglected by management.     

The certainty of judgments in health evaluations

Most evaluators seem to presume that all evaluative studies should result in conclusive evidence. Often, however, less than conclusive evidence may not only suffice, but be the only real alternative under conditions of limited evaluation resources. Three levels of evidence common to evaluation studies are discussed: suggestive evidence, preponderant evidence, and conclusive evidence. Ten factors are also presented which can be used to determine the level of certainty appropriate for a given evaluation study. Consideration of these factors enables the evaluator to specify when less than conclusive evidence is acceptable.     

Public opinion and the privatization of welfare: some theoretical implications

The social policy of the Thatcher government is characterized by an abrupt shift in the direction of the private sector. To what extent does this reflect what people want? The Institute of Economic Affairs conclude from the only suitable national opinion survey that such a move is strongly supported. Our reanalysis of their data shows that this strand in public opinion can coexist with, and need not contradict, an equal public enthusiasm for state welfare. Such results have important implications for our understanding of social policy. We conclude, therefore, with a discussion of contrasting marxist and liberal accounts which seeks to show that the evidence of ambivalence in popular attitudes about the welfare state supports particular developments in theory.     

Using Technology to Facilitate Collaboration in Community-Based Participatory Research (CBPR)

This study explores the use of Computer-Supported Collaborative Work (CSCW) technologies, by way of a computer-based system called iCohere. This system was used to facilitate collaboration conducting Community-Based Participatory Research (CBPR). Data was gathered from 13 members of a Community Collaborative Board (CCB). Analysis revealed that iCohere served the following functions: facilitating communication, providing a depository for information and resource sharing, and allowing for remote meeting attendance. Results indicated that while iCohere was useful in performing these functions, less expensive technologies had the potential to achieve similar goals if properly implemented. Implications for future research on CSCW systems and CBPR are discussed.     

Ambulance allocation for maximal survival with heterogeneous outcome measures

This paper proposes new models for locating emergency medical services (EMS) by incorporating survival functions for capturing multiple-classes of heterogeneous patients. The Maximal Expected Survival Location Model for Heterogeneous Patients (MESLMHP) aims to maximize the overall expected survival probability of multiple-classes of patients, whereby different classes could be defined according to agreed patient categories based on response time targets, or by capturing differing medical conditions each with a corresponding survival function. Furthermore, we propose and demonstrate an approximation approach to solving the extended stochastic version of MESLMHP, which utilizes queuing theory to permit the modeling of congestion and utilization at each ambulance station, and does not require assumptions to be made on the utilization of ambulances. Both models are demonstrated using data from the ambulance service in Wales. We show that our multiple outcome measures and survival-maximizing approach, rather than one based on average response time targets alone or a single patient class provides more effective EMS ambulance allocations.