Muon (g-2) Technical Design Report

The Muon (g-2) Experiment, E989 at Fermilab, will measure the muon anomalous magnetic moment a factor-of-four more precisely than was done in E821 at the Brookhaven National Laboratory AGS. The E821 result appears to be greater than the Standard-Model prediction by more than three standard deviations. When combined with expected improvement in the Standard-Model hadronic contributions, E989 should be able to determine definitively whether or not the E821 result is evidence for physics beyond the Standard Model. After a review of the physics motivation and the basic technique, which will use the muon storage ring built at BNL and now relocated to Fermilab, the design of the new experiment is presented. This document was created in partial fulfillment of the requirements necessary to obtain DOE CD-2/3 approval

Capture-recapture and multiple-record systems estimation II: Applications in human diseases

This article evaluates the potential epidemiologic uses of capture- recapture, which include the primary area of determining disease frequency. Capture-recapture may be a means to effectively 'count' new cases (incidence) or count existing cases (prevalence). Specific applications of capture- recapture in epidemiology are presented, one of which is its use in estimating death rates in a region close to Calcutta, India. The method also has considerable potential to assess suicides, and it may be the only technique to assess disease frequency in developing countries. In addition to generating an estimate of population size, another application of capture- recapture is to assess the costs of ascertainment relative to the degree of accuracy. This approach provides a formal means for assessing the cost- benefits of lists for the identification of cases. The authors believe that with careful and appropriate use, capture-recapture methods will provide a new approach that can considerably improve our ability to monitor disease.link_to_subscribed_fulltex

Capture-recapture and multiple-record systems estimation I: History and theoretical development

This paper reviews the historical background and the theoretical development of models for the analysis of data from capture-recapture or multiple-record systems for estimating the size of closed populations. The models and methods were originally developed for use in fisheries and wildlife biology and were later adapted for use in connection with human populations. Application to epidemiology came much later. The simplest capture-recapture model involves two lists or samples and has four key assumptions; that the population is closed, that individuals can be matched from capture to recapture, that capture in the second sample is independent of capture in the first sample, and that the capture probabilities are homogeneous across all individuals in the population. Log-linear models provide a convenient representation for this basic capture-recapture model and its extensions to K lists. The paper provides an overview for these models and illustrates how they allow for dependency among the lists and heterogeneity in the population. The use of log-linear models for estimation in the presence of both dependence and heterogeneity is illustrated on a four-list example involving ascertainment of diabetes using data gathered in 1988 from residents of Casale Monferrato, Italy. The final section of the paper discusses techniques for model selection in the context of models for estimating the size of populations.link_to_subscribed_fulltex