Diversity and equality: Race and class in America

Discussions of diversity, multiculturalism, and democracy often neglect the historical and structural economic and political inequalities embedded in these racial/ethnic/cultural differences among peoples in America. In this article we present a historical materialist analysis of African Americans and other oppressed peoples within the context of capitalist development. The current period of the electronic revolution and the labor displacing technology of the postindustrial era is creating the conditions for the erosion of the reform based social contract, and for heightened degrees of economic and political polarization, often expressed as racial polarization. At the same time, the abundance created by the high technology revolution contains the possibility of realizing equality and democracy for African Americans and for all of the American peoples.An earlier version of this paper was presented at the 1992 annual meetings of the American Sociological Association in Pittsburgh, Pennsylvania.     

Quality of life after radiation therapy: A study of 309 cancer survivors

(1) Comparison of patients with a national sample reveals no difference in income (adjusted for inflation), marital status and education level but patients, who are typically older, are more often retired or disabled. (2) Overall, perceived quality of life is nearly the same for patients and national sample; apparent differences can be readily explained by factors other than cancer or its treatment. (3) While some minor differences among patients were found as a function of their site of cancer, treatment modality, or health status, no evidence was found of significant detrimental effects due to radiation therapy or perceived quality of life. (4) Contrary to expectations of deteriorated quality of life, compared to the national baselines the patients are actually more satisfied with their lives as a whole.     

Patterns of Social Support in the Middle Childhood to Early Adolescent Transition: Implications for Adjustment

Children's social networks often include close family members, extended family members, and friends, but little is known about interindividual differences in the patterning of support from these sources. In this study, we used person‐oriented analyses to differentiate patterns of support for children undergoing the transition to adolescence. Social network and adjustment data were collected for an ethnically diverse sample of 691 fourth‐ and sixth‐grade children, with a two‐year follow‐up. Cluster analyses identified one pattern of support from both close family members and friends, a second pattern of support from both close and extended family members, and a third pattern of support primarily from close family members alone. Participants receiving support from close family in combination with either extended family or friends were better adjusted than were those without multiple support resources. The results suggest that a meaningful typology of children's social networks can be developed.     

Multiple imputation for combining confidential data owned by two agencies

Summary.  Statistical agencies that own different databases on overlapping subjects can benefit greatly from combining their data. These benefits are passed on to secondary data analysts when the combined data are disseminated to the public. Sometimes combining data across agencies or sharing these data with the public is not possible: one or both of these actions may break promises of confidentiality that have been given to data subjects. We describe an approach that is based on two stages of multiple imputation that facilitates data sharing and dissemination under restrictions of confidentiality. We present new inferential methods that properly account for the uncertainty that is caused by the two stages of imputation. We illustrate the approach by using artificial and genuine data.     

Underground storage tanks (UST): A closer investigation statistical implications to changing the shape of a UST

ABSTRACT

Gasoline service stations that use underground storage tanks (UST) assume that the manufactured tank is an ideal cylindrical shape. This cross-sectional shape plays a crucial role in determining a functional form for the volume of liquid that remains inside the tank. In industry, these formulas are used to compute strapping charts. But realistically, the manufacture, assembly, and installation of a tank may have deviation from the actual tank design (for which strapping charts had been developed). A theoretical volume function (based on tank dimensions) is used alongside of statistical methodology to reconcile volume differences in gasoline dispensed at the pump meters versus that displaced inside the tank. Statistical inventory reconciliation of this nature falls within the family of leak detection methods approved by the EPA (Environmental Protection Agency) and the California Water Resources Board. This methodology can also be used to assess deformation of the cross-sectional shape of the tank. We consider a deformation to an ellipse. Through simulation, we estimate the tank dimensions based on a nonlinear model with normal errors. The use of normal errors naturally facilitates a likelihood ratio test. Through this exploration, an approximation function is developed to help improve the power of the likelihood ratio test.     

Comments on estimators based on error in the predicted distribution function

In estimation of percentiles in the exponential distribution, the distribution function evaluated at the estimated percentile is often evaluated for purposes of warranty considerations. Optimal estimators are discussed and compared on their error in the predicted distribution function. Inconsistency is shown to exist between measures of closeness and measures of risk in the predicted distribution function. An optimal estimator based on absolute loss in the predicted distribution function is obtained and shown to be superior in measures of closeness to the optimal estimator, which minimizes squared error loss in the predicted distribution function.     

Body art,deviance, and American college students

This research examines the relationship between body art (tattoos and piercings) and deviance. With the increasing mainstream presence of visible tattoos and piercings among entertainers, athletes, and even in corporate boardrooms, we wonder the extent to which long-time enthusiasts and collectors regard the phenomenon as encroachment. We use sub-cultural identity theory to propose that individuals with increasing evidence of body art procurement will also report higher levels of deviant behavior in order to maintain and/or increase social distance from the mainstream. We tested this proposition by surveying 1753 American college students, asking them to report their level of body art acquisition and their history of deviance. Results indicate that respondents with four or more tattoos, seven or more body piercings, or piercings located in their nipples or genitals, were substantively and significantly more likely to report regular marijuana use, occasional use of other illegal drugs, and a history of being arrested for a crime. Less pronounced, but still significant in many cases, was an increased propensity for those with higher incidence of body art to cheat on college work, binge drink, and report having had multiple sex partners in the course of their lifetime.     

Secure Bayesian model averaging for horizontally partitioned data

When multiple data owners possess records on different subjects with the same set of attributes—known as horizontally partitioned data—the data owners can improve analyses by concatenating their databases. However, concatenation of data may be infeasible because of confidentiality concerns. In such settings, the data owners can use secure computation techniques to obtain the results of certain analyses on the integrated database without sharing individual records. We present secure computation protocols for Bayesian model averaging and model selection for both linear regression and probit regression. Using simulations based on genuine data, we illustrate the approach for probit regression, and show that it can provide reasonable model selection outputs.