What is educational entrepreneurship? Strategic action,temporality, and the expansion of US higher education

Theory and Society - The massive expansion of US higher education after World War II is a sociological puzzle: a spectacular feat of state capacity-building in a highly federated polity. Prior...     

A Bayesian method for classification and discrimination

We discuss Bayesian analyses of traditional normal-mixture models for classification and discrimination. The development involves application of an iterative resampling approach to Monte Carlo inference, commonly called Gibbs sampling, and demonstrates routine application. We stress the benefits of exact analyses over traditional classification and discrimination techniques, including the ease with which such analyses may be performed in a quite general setting, with possibly several normal-mixture components having different covariance matrices, the computation of exact posterior classification probabilities for observed data and for future cases to be classified, and posterior distributions for these probabilities that allow for assessment of second-level uncertainties in classification.     

Low dose risk estimation via simultaneous statistical inferences

Summary.  The paper develops and studies simultaneous confidence bounds that are useful for making low dose inferences in quantitative risk analysis. Application is intended for risk assessment studies where human, animal or ecological data are used to set safe low dose levels of a toxic agent, but where study information is limited to high dose levels of the agent. Methods are derived for estimating simultaneous, one-sided, upper confidence limits on risk for end points measured on a continuous scale. From the simultaneous confidence bounds, lower confidence limits on the dose that is associated with a particular risk (often referred to as a bench-mark dose ) are calculated. An important feature of the simultaneous construction is that any inferences that are based on inverting the simultaneous confidence bounds apply automatically to inverse bounds on the bench-mark dose.     

Benchmark Analysis: Shopping with Proper Confidence

We discuss the issue of using benchmark doses for quantifying (excess) risk associated with exposure to environmental hazards. The paradigm of low-dose risk estimation in dose-response modeling is used as the primary application scenario. Emphasis is placed on making simultaneous inferences on benchmark doses when data are in the form of proportions, although the concepts translate easily to other forms of outcome data.     

Asylum Seeking in Australia

The rise in the number of asylum seekers in Australia presents considerable challenges to the state as they are a self‐selected, demand‐driven group, whose numbers, country of origin, ethnic background, and social demographic characteristics cannot be determined in advance of their arrival. People who apply for protection at the border are regarded primarily as illegal immigrants, and only secondarily as asylum seekers, and the illegality of their entry has become the primary factor in the way they are treated by the state, rather than their need for protection. Two streams of asylum seekers and two streams of refugees have been created. There are marked differences in the treatment given while claims for protection are examined and once decisions have been made in their favor. This article examines the development of asylum policy in Australia and sets the discussion within a review of the number of people who have applied for and been granted protection in recent years.     

The influence of risk and protective factors on burnout experienced by those who work with maltreated children

The aim of the study was to explore the degree (and type) of burnout and trauma symptoms, personal histories and coping strategies retrospectively reported by those who work with maltreated children and their families. A self‐selected sample of workers (N = 44) completed a self‐report questionnaire assessing childhood maltreatment, family background characteristics, current adjustment, coping strategies and burnout. Workers reported high levels of emotional exhaustion and depersonalization, and a low to moderate sense of personal accomplishment. Family background characteristics predicted the occurrence of maltreatment and current adjustment, and a personal history of maltreatment predicted current trauma symptoms, but not burnout. Workers most frequently used problem‐focused coping strategies and sought social support; however, coping strategies were not associated with the level of either trauma symptoms or burnout. Despite employing positive coping strategies, their efficacy may be affected by other interpersonal, intra‐individual and job resource issues. Copyright © 2002 John Wiley & Sons, Ltd.     

Case study in the Bayesian analysis of a cost‐effectiveness trial in the evaluation of health care technologies: Depression

We present a case study based on a depression study that will illustrate the use of Bayesian statistics in the economic evaluation of cost‐effectiveness data, demonstrate the benefits of the Bayesian approach (whilst honestly recognizing any deficiencies) with respect to frequentist methods, and provide details of using the methods, including computer code where appropriate. Copyright © 2003 John Wiley & Sons, Ltd.     

Population structure and correlation between auxiliary and target variables may affect precision of estimates in forest inventory

Simulations of forest inventory in several populations compared simple random with “quick probability proportional to size” (QPPS) sampling. The latter may be applied in the absence of a list sampling frame and/or prior measurement of the auxiliary variable. The correlation between the auxiliary and target variables required to render QPPS sampling more efficient than simple random sampling varied over the range 0.3–0.6 and was lower when sampling from populations that were skewed to the right. Two possible analytical estimators of the standard error of the estimate of the mean for QPPS sampling were found to be less reliable than bootstrapping.