Reference range: Which statistical intervals to use?

Reference ranges, which are data-based intervals aiming to contain a pre-specified large proportion of the population values, are powerful tools to analyse observations in clinical laboratories. Their main point is to classify any future observations from the population which fall outside them as atypical and thus may warrant further investigation. As a reference range is constructed from a random sample from the population, the event ‘a reference range contains (100 P)% of the population’ is also random. Hence, all we can hope for is that such event has a large occurrence probability. In this paper we argue that some intervals, including the P prediction interval, are not suitable as reference ranges since there is a substantial probability that these intervals contain less than (100 P)% of the population, especially when the sample size is large. In contrast, a (P,γ) tolerance interval is designed to contain (100 P)% of the population with a pre-specified large confidence γ so it is eminently adequate as a reference range. An example based on real data illustrates the paper’s key points

Justicia cordial.

Madrid: Editorial Trotta, 2010. 149 pp

Light-Trap: A SiPM Upgrade for Very High Energy Astronomy and Beyond

With the development of the Imaging Atmospheric Cherenkov Technique (IACT), Gamma-ray astronomy has become one of the most interesting and productive fields of astrophysics. Current IACT telescope arrays (MAGIC, H.E.S.S, VERITAS) use photomultiplier tubes (PMTs) to detect the optical/near-UV Cherenkov radiation emitted due to the interaction of gamma rays with the atmosphere. For the next generation of IACT experiments, the possibility of replacing the PMTs with Silicon photomultipliers (SiPMs) is being studied. Among the main drawbacks of SiPMs are their limited active area (leading to an increase in the cost and complexity of the camera readout) and their sensitivity to unwanted wavelengths. Here we propose a novel method to build a relatively low-cost pixel consisting of a SiPM attached to a PMMA disc doped with a wavelength shifter. This pixel collects light over a much larger area than a single standard SiPM and improves sensitivity to near-UV light while simultaneously rejecting background. We describe the design of a detector that could also have applications in other fields where detection area and cost are crucial. We present results of simulations and laboratory measurements of a pixel prototype and from field tests performed with a 7-pixel cluster installed in a MAGIC telescope camera.Comment: Proceedings of the 35th International Cosmic Ray Conference (ICRC 2017), Bexco, Busan, Korea. Id:81

Classification Performance of Neural Networks Versus Logistic Regression Models: Evidence From Healthcare Practice

Machine learning encompasses statistical approaches such as logistic regression (LR) through to more computationally complex models such as neural networks (NN). The aim of this study is to review current published evidence for performance from studies directly comparing logistic regression, and neural network classification approaches in medicine. A literature review was carried out to identify primary research studies which provided information regarding comparative area under the curve (AUC) values for the overall performance of both LR and NN for a defined clinical healthcare-related problem. Following an initial search, articles were reviewed to remove those that did not meet the criteria and performance metrics were extracted from the included articles. Teh initial search revealed 114 articles; 21 studies were included in the study. In 13/21 (62%) of cases, NN had a greater AUC compared to LR, but in most the difference was small and unlikely to be of clinical significance; (unweighted mean difference in AUC 0.03 (95% CI 0-0.06) in favour of NN versus LR. In the majority of cases examined across a range of clinical settings, LR models provide reasonable performance that is only marginally improved using more complex methods such as NN. In many circumstances, the use of a relatively simple LR model is likely to be adequate for real-world needs but in specific circumstances in which large amounts of data are available, and where even small increases in performance would provide significant management value, the application of advanced analytic tools such as NNs may be indicated

Low-energy cross section of the 7Be(p,g)8B solar fusion reaction from Coulomb dissociation of 8B

Final results from an exclusive measurement of the Coulomb breakup of 8B into 7Be+p at 254 A MeV are reported. Energy-differential Coulomb-breakup cross sections are analyzed using a potential model of 8B and first-order perturbation theory. The deduced astrophysical S_17 factors are in good agreement with the most recent direct 7Be(p,gamma)8B measurements and follow closely the energy dependence predicted by the cluster-model description of 8B by Descouvemont. We extract a zero-energy S_17 factor of 20.6 +- 0.8 (stat) +- 1.2 (syst) eV b.Comment: 14 pages including 16 figures, LaTeX, accepted for publication in Physical Review C. Minor changes in text and layou

Fragmentation of exotic oxygen isotopes

Abrasion-ablation models and the empirical EPAX parametrization of projectile fragmentation are described. Their cross section predictions are compared to recent data of the fragmentation of secondary beams of neutron-rich, unstable 19,20,21O isotopes at beam energies near 600 MeV/nucleon as well as data for stable 17,18O beams