The campus of the George Washington University (GW), originated on College Hill, a site bounded by 14th Street, Columbia Road, 15th Street and Florida Avenue, NW in the Columbia Heights neighborhood of Washington, DC. After relocating to the downtown financial district in the 1880s and then to Foggy Bottom in 1912, GW now has three campuses. Foggy Bottom is the location of the university's main campus in Washington, DC. Also in Washington's Foxhall neighborhood is the Mount Vernon Campus, formerly the Mount Vernon College for Women. Additionally, the George Washington University Virginia Campus is located in Ashburn, VA.
The estimation of conditional quantiles at extreme tails is of great interest in numerous applications. Various methods that integrate regression analysis with an extrapolation strategy derived from extreme value theory have been proposed to estimate extreme conditional quantiles in scenarios with a fixed number of covariates. However, these methods prove ineffective in high-dimensional settings, where the number of covariates increases with the sample size. In this article, we develop new estimation methods tailored for extreme conditional quantiles with high-dimensional covariates. We establish the asymptotic properties of the proposed estimators and demonstrate their superior performance through simulation studies, particularly in scenarios of growing dimension and high dimension where existing methods may fail. Furthermore, the analysis of auto insurance data validates the efficacy of our methods in estimating extreme conditional insurance claims and selecting important variables.
Modern medical research, such as dose-finding studies, seamless trials, and shared control designs, often involves comparing multiple treatments simultaneously. Despite its wide applications, most research focuses on continuous endpoints, leaving the inference for general outcome types in high demand. In this article, we propose a new inference method for conducting multiple-treatment comparisons involving endpoints within the generalized linear model (GLM) framework under covariate-adaptive randomization (CAR). First, we investigate the asymptotic properties of the standard Wald z-statistics (z-scores) in multi-arm trials, highlighting issues when the working model is misspecified, particularly through omitted covariates. Our theoretical findings reveal that these z-scores do not consistently converge to a standard multivariate normal distribution, leading to either conservative or inflated Type I error rates, depending on the specific GLM endpoint. Second, based on these theoretical results, we develop adjusted test statistics to correct the distributional problems. To appropriately control the family-wise Type I error rate inherent in multi-arm comparisons, we incorporate our adjusted statistics with Simes-type multiple-testing procedures. This robust inference method can effectively control Type I error while potentially improving power. Extensive simulation studies and a real-world application to a metastatic breast cancer trial confirm the effectiveness and practicality of our approach.
Saltwater intrusion (SWI) is rapidly transforming coastal agricultural landscapes through rising soil salinity, altered nutrient cycling, and declining crop productivity. On Maryland’s Lower Eastern Shore (USA), we examined how salinization affects nitrogen (N) in soils, porewater, and plants under land management strategies representing common farmer responses to SWI: perennial grass establishment, restoration, and abandonment. Across three saltwater-intruded farms and over three years, soil electrical conductivity (EC1:5) increased two- to fourfold, soil sodium (Na) four- to sixfold, and porewater electrical conductivity (EC) twofold, suggesting these fields are rapidly salinizing. Topsoil (0–10 cm) Na and EC1:5 were strongly correlated (R2 = 0.88), while relationships between topsoil Na and N were significant but modest (R2 = 0.33), suggesting that Na explained only part of the variation in soil N pools. Soil inorganic N (nitrate and ammonium) declined, indicating depletion of available N pools under progressing salinization. However, aboveground biomass N increased substantially under Panicum virgatum (perennial grass establishment) and Spartina patens (restoration), accumulating four times more N than abandoned plots. These results demonstrate that perennial grass systems can maintain productivity and accumulate greater aboveground biomass N, even as fields salinize. In contrast, abandoned fields exhibited lower biomass and reduced standing biomass N pools. Establishing salt-tolerant perennials therefore represents an effective strategy for coastal farms transitioning due to sea-level rise and SWI. These findings provide actionable guidance for easement and conservation programs seeking to support adaptive management of salinizing agricultural lands.
Intersectionality theory suggests that because stigma arises from the interplay of multiple marginalized identities, Black women with obesity may face stronger negative attitudes than White women when using GLP-1 agonists, a newer class of obesity medications often perceived as an 'easy way out.' This experimental study tested how exposure to different weight loss methods affected stigma toward a Black or White woman with obesity, as well as the influence of participant race on stigma. A sample of 402 Black and White women with overweight or obesity were randomly assigned to read about a Black or White woman named Evette who lost 15% of her total body weight with either diet/exercise or a GLP-1. Participants reported stigmatizing attitudes toward Evette (fat phobia, dislike, desire for social distance, and blame) and beliefs that she took a weight loss shortcut. Stigma was higher when Evette lost weight with a GLP-1 (vs. diet/exercise) and, contrary to hypotheses, when Evette was depicted as White (vs. Black). Moderated mediation analyses demonstrated that GLP-1-assisted weight loss (vs. diet/exercise) led to higher fat phobia, dislike, desire for social distance, and blame via stronger shortcut beliefs and this effect was more pronounced when Evette was portrayed as White. Participant race did not influence how weight loss with a GLP-1 and Evette's race, together, affected stigma through shortcut beliefs. Findings highlight the importance of challenging societal narratives about what constitutes 'acceptable' weight loss strategies for women with obesity to reduce stigma and protect long-term health.
