Racial Attitudes in the Deep South: Persistence and Change at the University of Alabama, 1963–2013*

Using data from a unique series of surveys collected between 1963 and 2013, this study examines racial attitudes among young white adults in the Deep South over a 50-year period. Repeated surveys of University of Alabama students in 1963, 1966, 1969, 1972, 1983, 1988, and 2013 measured racial stereotypes, support for racial segregation, and in the 2013 study, racial resentment and support for ameliorative racial policies. Analyses show that in the 1960s endorsement of racial stereotypes was a powerful predictor of support for racial segregation. By the early 1970s, racial integration became a reality in the Deep South and, paralleling broad trends in U.S. society, endorsement of racial stereotypes and support for racial segregation declined. Simultaneously, threats to whites' position in the form of ameliorative racial policies (including affirmative action) emerged along with racial resentment. By 2013, racial resentment, rather than racial stereotyping, was the primary determinant of white students' opposition to racial change. Our findings support Herbert Blumer's (1958) argument that racial prejudice exists in a sense of group position, and that it functions to preserve the advantaged position of the dominant group regardless of changes in the form that prejudice takes.     

The Role of Government in Macro-Level Quality Development: A Case Study of South Korea

Public Organization Review - This study investigates the South Korean government’s effort to promote macro-level quality development. Using the single case study method, the authors examined...     

Natural cubic splines for the analysis of Alzheimer's clinical trials

Mixed model repeated measures (MMRM) is the most common analysis approach used in clinical trials for Alzheimer's disease and other progressive diseases measured with continuous outcomes over time. The model treats time as a categorical variable, which allows an unconstrained estimate of the mean for each study visit in each randomized group. Categorizing time in this way can be problematic when assessments occur off-schedule, as including off-schedule visits can induce bias, and excluding them ignores valuable information and violates the intention to treat principle. This problem has been exacerbated by clinical trial visits which have been delayed due to the COVID19 pandemic. As an alternative to MMRM, we propose a constrained longitudinal data analysis with natural cubic splines that treats time as continuous and uses test version effects to model the mean over time. Compared to categorical-time models like MMRM and models that assume a proportional treatment effect, the spline model is shown to be more parsimonious and precise in real clinical trial datasets, and has better power and Type I error in a variety of simulation scenarios.     

A multivariate extension of the Lorenz curve based on copulas and a related multivariate Gini coefficient

The Journal of Economic Inequality - We propose an extension of the univariate Lorenz curve and of the Gini coefficient to the multivariate case, i.e., to simultaneously measure inequality in more...