RAND Corporation

About: RAND Corporation is a nonprofit organization based out in Santa Monica, California, United States. It is known for research contribution in the topics: Population & Health care. The organization has 9602 authors who have published 18570 publications receiving 744658 citations.

Utilization of mental health and substance abuse services among homeless adults in los angeles

Abstract: Objectives.Even though psychiatric disorders are disproportionately present among the homeless, little is known about the extent to which homeless people receive treatment for those problems or the factors that are associated with receiving treatment. This article examines utilization and predictors

Financial Illiteracy and Stock Market Participation: Evidence from the RAND American Life Panel

Abstract: Financially unsophisticated consumers who consistently make sub-optimal financial decisions may suffer lasting consequences for long-term wealth accumulation and welfare. This paper focuses attention on a well-documented area of potentially suboptimal financial decision making: the lack of stock market participation. Using a broad-based assessment of financial literacy administered to a sample of older American respondents in the RAND American Life Panel (ALP), we use a novel strategy for establishing causation between stock-market related financial literacy and stock market participation, using knowledge of other financial topics as instrumental variables. We find that ignorance of stock market investment knowledge significantly reduces propensity to hold stocks. In particular, a decrease of one-standard deviation in the relevant measure suggests a decrease on the order of 10% in participation.

Predicting the Appropriate Use of Carotid Endarterectomy, Upper Gastrointestinal Endoscopy, and Coronary Angiography

Abstract: Background and Methods. In a nationally representative population 65 years of age or older, we have demonstrated that about one quarter of coronary angiographies and upper gastrointestinal endoscopies and two thirds of carotid endarterectomies were performed for reasons that were less than medically appropriate. In this paper we examine whether specific characteristics of patients (age, sex, and race), physicians (age, board-certification status, and experience with the procedure), or hospitals (teaching status, profit-making status, and size) predict whether a procedure will be performed appropriately. Results. In general, we found that little of the variability in the appropriateness of care (4 percent or less) could be explained on the basis of standard, easily obtainable data about the patient, the physician, or the hospital. For all three procedures, however, performance in a teaching hospital increased the likelihood that the reasons would be medically appropriate (P = 0.09 for angiography,...

A Collaborative Training Algorithm for Distributed Learning

Abstract: In this paper, an algorithm is developed for collaboratively training networks of kernel-linear least-squares regression estimators. The algorithm is shown to distributively solve a relaxation of the classical centralized least-squares regression problem. A statistical analysis shows that the generalization error afforded agents by the collaborative training algorithm can be bounded in terms of the relationship between the network topology and the representational capacity of the relevant reproducing kernel Hilbert space. Numerical experiments suggest that the algorithm is effective at reducing noise. The algorithm is relevant to the problem of distributed learning in wireless sensor networks by virtue of its exploitation of local communication. Several new questions for statistical learning theory are proposed.