Metropolitan Structure and Neighborhood Attainment: Exploring Intermetropolitan Variation in Racial Residential Segregation

Using data from the 1981, 1991, and 2001 waves of the Panel Study of Income Dynamics and several decennial censuses, we examine how characteristics of metropolitan areas are associated with black and white households’ neighborhood racial composition. Results from hierarchical linear models show that about 20% to 40% of the variation in the percentage of households’ tract population that is non-Hispanic white or non-Hispanic black exists across metropolitan areas. Over time, white households’ exposure to non-Hispanic white neighbors has declined, and their exposure to non-Hispanic black neighbors has increased; the reverse trends are observed for blacks. These trends cannot be attributed to changes in the ecological structure of metropolitan areas. Blacks have fewer white neighbors in large metropolitan areas containing sizable minority populations, and blacks have more white neighbors in metropolitan areas with high government employment. Whites have more black neighbors in metropolitan areas with high levels of government employment and ample new housing; whites have fewer black neighbors in metropolitan areas with a high level of municipal fragmentation. The association between metropolitan-area percentage black and tract percentage black is weaker among whites than among blacks, suggesting that whites are especially motivated to self-segregate in metropolitan areas with large black populations.     

Semiparametric Stochastic Modeling of the Rate Function in Longitudinal Studies

In longitudinal biomedical studies, there is often interest in the rate functions, which describe the functional rates of change of biomarker profiles. This paper proposes a semiparametric approach to model these functions as the realizations of stochastic processes defined by stochastic differential equations. These processes are dependent on the covariates of interest and vary around a specified parametric function. An efficient Markov chain Monte Carlo algorithm is developed for inference. The proposed method is compared with several existing methods in terms of goodness-of-fit and more importantly the ability to forecast future functional data in a simulation study. The proposed methodology is applied to prostate-specific antigen profiles for illustration. Supplementary materials for this paper are available online.     

Bayesian and likelihood inference for cure rates based on defective inverse Gaussian regression models

Failure time models are considered when there is a subpopulation of individuals that is immune, or not susceptible, to an event of interest. Such models are of considerable interest in biostatistics. The most common approach is to postulate a proportion p of immunes or long-term survivors and to use a mixture model [5]. This paper introduces the defective inverse Gaussian model as a cure model and examines the use of the Gibbs sampler together with a data augmentation algorithm to study Bayesian inferences both for the cured fraction and the regression parameters. The results of the Bayesian and likelihood approaches are illustrated on two real data sets.     

Female Authority and Dominion: Discourse and Distinctions of Heavy Metal Scholarship

From its inception, both outsiders and insiders have associated heavy metal with men and masculinity. Some have even maintained that metal culture is hostile territory for women. Despite this, a significant proportion of writers who have documented, analysed, and indeed celebrated heavy metal has been women, from the groundbreaking sociological studies of Deena Weinstein and Donna Gaines, to the recent ethnographic work of Emma Baulch. This article provides a preliminary investigation of this historical phenomenon and what it can reveal about the ever complex, constantly changing relationship between gender and power in metal.     

Public support for Hispanic deportation in the United States: the effects of ethnic prejudice and perceptions of economic competition in a period of economic distress

This paper investigates the effect of ethnic prejudice and perceived economic competition on support for deportation and alternative policy options concerning the handling of undocumented immigrants. Using a national survey conducted in early 2009, data are analysed using bivariate and multinomial regression techniques. Ethnic prejudice and perceived economic competition were found to be significantly related to support for deportation in the face of alternative options, controlling for the effects of age, sex, employment status, nativity, race, party identification, and education. Furthermore, majority support for deportation was found among conservatives, moderates, Republicans, and Independents. Even among liberals and Democrats, substantial numbers supported deportation. During the recent economic recession, perceived economic competition and ethnic prejudice were dominant influences on deportation preferences, and deportation appears to have become a mainstream policy option. However, we speculate that deportation preferences are relatively shallow and unstable owing partly to the dependence of immigration public opinion on economic cycles, and, ultimately, the unfeasibility of deportation as a policy option.