Status claims, performance expectations, and inequality in groups

We state and test two new theoretical assumptions regarding effects of explicit status claims upon others' performance expectations and the consequent group hierarchy: (1) that any such claim is aggregated with other status information, and (2) that the weight of the effect of a claim is a direct function of the status position of the person expressing it. Added to the core assumptions of theories of status generalization, the new assumptions account for phenomena also called “second-order expectations” and “status cues.” Results from a six-condition experimental test support the ideas, and permit comparing our assumptions with two variant mechanisms. We consider some uses of the extended theory, including interventions to control status effects within groups and legitimating and de-legitimating group hierarchies.     

Bayesian analysis of screening data: Application to AIDS in blood donors

The rapid increase in the number of AIDS cases during the 1980s and the spread of the disease from the high-risk groups into the general population has created widespread concern. In particular, assessing the accuracy of the screening tests used to detect antibodies to the HIV (AIDS) virus in donated blood and determining the prevalance of the disease in the population are fundamental statistical problems. Because the prevalence of AIDS varies widely by geographic region and data on the number of infected blood donors are published regularly, Bayesian methods, which utilize prior results and update them as new data become available, are quite useful. In this paper we develop a Bayesian procedure for estimating the prevalence of a rare disease, the sensitivity and specificity of the screening tests, and the predictive value of a positive or negative screening test. We apply the procedure to data on blood donors in the United States and in Canada. Our results augment those described in Gastwirth (1987) using classical methods. Indeed, we show that the inclusion of sound prior knowledge into the statistical analysis does not yield sufficiently precise estimates of the predictive value of a positive test. Hence confirmatory testing is needed to obtain reliable estimates. The emphasis of the Bayesian predictive paradigm on prediction intervals for future data yields a valuable insight. We demonstrate that using them might have detected a decline in the specificity of the most frequently used screening test earlier than it apparently was.     

The effects of quality of working life (QWL) on employee behavioral responses

Quality of work life (QWL) was conceptualized in terms of need satisfaction stemming from an interaction of workers' needs (survival, social, ego, and self-actualization needs) and those organizational resources relevant for meeting them. It was hypothesized that need satisfaction (or QWL) is positively related to organizational identification, job satisfaction, job involvement, job effort, job performance; and negatively related to personal alienation. A survey study was conducted based on a sample of 219 service deliverers to the elderly in a large midwestern city. The results were consistent with the hypotheses. Managerial implications were also discussed.     

The flood control saga in the Passaic River Basin

Flooding is a natural phenomenon which engineers and politicians have attempted to control since the beginning of time. The Passaic River Basin in northern New Jersey has been recognized as a significant floodprone area in the United States since colonial times. Several State and U.S. Army Corps of Engineers proposals have been abandoned because of both economic and environmental objections to expensive public works projects. During the early part of the Twentieth Century, houses were built in the floodway of the Passaic River, an area where lives and personal belongings were at highest risk.The Army Corps of Engineers has proposed a $1.0 billion flood control tunnel plan while a local watershed association, the Passaic River Coalition, has recommmended a buy-out of the houses at highest risk at a cost of $103 million. This paper introduces that innovative concept for flood management—relocating people out of the rivers path—in the most urban area in the United States.     

Social Class and Delinquency: One More Time*

The diversity of findings on the class-delinquency relationship may reflect differential middle-class cultural dominance in school systems. In predominantly middle-class schools, the minority of working-class youth conform to the majority standards and the relationship does not hold. In more class heterogeneous schools a cross-class cultural diffusion occurs among youth such that objective class status no longer is predictive of delinquency. In predominantly working-class schools a negative class-delinquency relationship is found; in such a milieu, those youth who are committed to conventional middle-class culture only can have acquired such commitments from their middle-class parents. The self-report studies of class and delinquency are reviewed in the light of these hypotheses.     

Criteria for Linear Model Selection Based on Kullback's Symmetric Divergence

Model selection criteria are frequently developed by constructing estimators of discrepancy measures that assess the disparity between the 'true' model and a fitted approximating model. The Akaike information criterion (AIC) and its variants result from utilizing Kullback's directed divergence as the targeted discrepancy. The directed divergence is an asymmetric measure of separation between two statistical models, meaning that an alternative directed divergence can be obtained by reversing the roles of the two models in the definition of the measure. The sum of the two directed divergences is Kullback's symmetric divergence. In the framework of linear models, a comparison of the two directed divergences reveals an important distinction between the measures. When used to evaluate fitted approximating models that are improperly specified, the directed divergence which serves as the basis for AIC is more sensitive towards detecting overfitted models, whereas its counterpart is more sensitive towards detecting underfitted models. Since the symmetric divergence combines the information in both measures, it functions as a gauge of model disparity which is arguably more balanced than either of its individual components. With this motivation, the paper proposes a new class of criteria for linear model selection based on targeting the symmetric divergence. The criteria can be regarded as analogues of AIC and two of its variants: 'corrected' AIC or AICc and 'modified' AIC or MAIC. The paper examines the selection tendencies of the new criteria in a simulation study and the results indicate that they perform favourably when compared to their AIC analogues.