Alicia Carriquiry – författare

The U.S. Department of Homeland Security (DHS) is responsible for securing and managing the nation's borders. Over the past decade, DHS has dramatically stepped up its enforcement efforts at the U.S.-Mexico border, increasing the number of U.S. Border patrol (USBP) agents, expanding the deployment of technological assets, and implementing a variety of "consequence programs" intended to deter illegal immigration. During this same period, there has also been a sharp decline in the number of unauthorized migrants apprehended at the border. Trends in total apprehensions do not, however, by themselves speak to the effectiveness of DHS's investments in immigration enforcement. In particular, to evaluate whether heightened enforcement efforts have contributed to reducing the flow of undocumented migrants, it is critical to estimate the number of border-crossing attempts during the same period for which apprehensions data are available. With these issues in mind, DHS charged the National Research Council (NRC) with providing guidance on the use of surveys and other methodologies to estimate the number of unauthorized crossings at the U.S.-Mexico border, preferably by geographic region and on a quarterly basis. Options for Estimating Illegal Entries at the U.S.-Mexico Border focuses on Mexican migrants since Mexican nationals account for the vast majority (around 90 percent) of attempted unauthorized border crossings across the U.S.-Mexico border.

The series of workshops Case Studies in Bayesian Statistics at Carnegie Mellon University is unique in devoting an entire meeting to extended presentation and discussion of scientific investigations in which statisticians play central roles within integrated, cross- disciplinary teams. The goal has been to elucidate the interplay between Bayesian theory and practice, and thereby identify successful methods and indicate important directions for future research. This volume contains the four invited case studies, with accompanying discussion, and nine contributed papers, from the 4th workshop, which was held September 27-28, 1997. While most of the case studies in this volume come from biomedical research, the reader will also find studies in environmental science and marketing research. Students and teachers of statistics, research statisticians, and investigators from other fields should find a wealth of ideas and methods in this series of case studies.

The 6th Workshop on Case Studies in Bayesian Statistics was held at the Carnegie Mellon University in October, 2001. This volume contains the invited case studies with the accompanying discussion as well as contributed papers selected by a refereeing process.