Four reasons to prefer Bayesian analyses over significance testing

Inference using significance testing and Bayes factors is compared and contrasted in five case studies based on real research. The first study illustrates that the methods will often agree, both in motivating researchers to conclude that H1 is supported better than H0, and the other way round, that H0 is better supported than H1. The next four, however, show that the methods will also often disagree. In these cases, the aim of the paper will be to motivate the sensible evidential conclusion, and then see which approach matches those intuitions. Specifically, it is shown that a high-powered non-significant result is consistent with no evidence for H0 over H1 worth mentioning, which a Bayes factor can show, and, conversely, that a low-powered non-significant result is consistent with substantial evidence for H0 over H1, again indicated by Bayesian analyses. The fourth study illustrates that a high-powered significant result may not amount to any evidence for H1 over H0, matching the Bayesian conclusion. Finally, the fifth study illustrates that different theories can be evidentially supported to different degrees by the same data; a fact that P-values cannot reflect but Bayes factors can. It is argued that appropriate conclusions match the Bayesian inferences, but not those based on significance testing, where they disagree

Green Sturgeon Physical Habitat Use in the Coastal Pacific Ocean

The green sturgeon (Acipenser medirostris) is a highly migratory, oceanic, anadromous species with a complex life history that makes it vulnerable to species-wide threats in both freshwater and at sea. Green sturgeon population declines have preceded legal protection and curtailment of activities in marine environments deemed to increase its extinction risk. Yet, its marine habitat is poorly understood. We built a statistical model to characterize green sturgeon marine habitat using data from a coastal tracking array located along the Siletz Reef near Newport, Oregon, USA that recorded the passage of 37 acoustically tagged green sturgeon. We classified seafloor physical habitat features with high-resolution bathymetric and backscatter data. We then described the distribution of habitat components and their relationship to green sturgeon presence using ordination and subsequently used generalized linear model selection to identify important habitat components. Finally, we summarized depth and temperature recordings from seven green sturgeon present off the Oregon coast that were fitted with pop-off archival geolocation tags. Our analyses indicated that green sturgeon, on average, spent a longer duration in areas with high seafloor complexity, especially where a greater proportion of the substrate consists of boulders. Green sturgeon in marine habitats are primarily found at depths of 20–60 meters and from 9.5–16.0°C. Many sturgeon in this study were likely migrating in a northward direction, moving deeper, and may have been using complex seafloor habitat because it coincides with the distribution of benthic prey taxa or provides refuge from predators. Identifying important green sturgeon marine habitat is an essential step towards accurately defining the conditions that are necessary for its survival and will eventually yield range-wide, spatially explicit predictions of green sturgeon distribution

Rationale and design of BISTRO: a randomized controlled trial to determine whether bioimpedance spectroscopy guided fluid management maintains residual kidney function in incident haemodialysis patients

Background: Preserved residual kidney function (RKF) and normal fluid status are associated with better patient outcomes in incident haemodialysis patients. The objective of this trial is to determine whether using bioimpedance technology in prescribing the optimal post-dialysis weight can reduce the rate of decline of RKF and potentially improve patient outcomes. Methods/Design: 516 patients commencing haemodialysis, aged >18 with RKF of > 3 ml/min/1.73 m2 or a urine volume >500 ml per day or per the shorter inter-dialytic period will be consented and enrolled into a pragmatic, open label, randomized controlled trial. The intervention is incorporation of bioimpedance spectroscopy (BI) determination of normally hydrated weight to set a post-dialysis target weight that limits volume depletion, compared to current standard practice. Clinicians and participants will be blinded to BI measures in the control group and a standardized record capturing management of fluid status will be used in all participants. Primary outcome is preservation of residual kidney function assessed as time to anuria (≤100 ml/day or ≤200 ml urine volume in the short inter-dialytic period). A sample size of 516 was based upon a cumulative incidence of 30% anuria in the control group and 20% in the treatment group and 11% competing risks (death, transplantation) over 10 months, with up to 2 years follow-up. Secondary outcomes include rate of decline in small solute clearance, significant adverse events, hospitalization, loss of vascular access, cardiovascular events and interventions, dialysis efficacy and safety, dialysis-related symptoms and quality of life. Economic evaluation will be carried out to determine the cost-effectiveness of the intervention. Analyses will be adjusted for patient characteristics and dialysis unit practice patterns relevant to fluid management. Discussion: This trial will establish the added value of undertaking BI measures to support clinical management of fluid status and establish the relationship between fluid status and preservation of residual kidney function in incident haemodialysis patients. Trial registration: ISCCTN Number: 11342007, completed 26/04/2016; NIHR Portfolio number: CPMS31766; Sponsor: Keele University Keywords: Fluid status, Body composition, Residual kidney function, Haemodialysis, Bioimpedance, Fluid management, Health economic

Immunology and genetics of type 1 diabetes

Type 1 diabetes is one of the most well-characterized autoimmune diseases. Type 1 diabetes compromises an individual's insulin production through the autoimmune destruction of pancreatic Β-cells. Although much is understood about the mechanisms of this disease, multiple potential contributing factors are thought to play distinct parts in triggering type 1 diabetes. The immunological diagnosis of type 1 diabetes relies primarily on the detection of autoantibodies against islet antigens in the serum of type 1 diabetes mellitus patients. Genetic analyses of type 1 diabetes have linked human leukocyte antigen, specifically class II alleles, to susceptibility to disease onset. Environmental catalysts include various possible factors, such as viral infections, although the evidence linking infections with type 1 diabetes remains inconclusive. Imbalances within the immune system's system of checks and balances may promote immune activation, while undermining immune regulation. A lack of proper regulation and overactive pathogenic responses provide a framework for the development of autoimmune abnormalities. Type 1 diabetes is a predictable and potentially treatable disease that still requires much research to fully understand and pinpoint the exact triggering events leading to autoimmune activation. In silico research can aid the comprehension of the etiology of complex disease pathways, including Type I diabetes, in order to and help predict the outcome of therapeutic strategies aimed at preserving Β-cell function. Mt Sinai J Med 75:314–327, 2008. © 2008 Mount Sinai School of MedicinePeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/60987/1/20052_ftp.pd

Managed Metapopulations: Do Salmon Hatchery ‘Sources’ Lead to In-River ‘Sinks’ in Conservation?

Maintaining viable populations of salmon in the wild is a primary goal for many conservation and recovery programs. The frequency and extent of connectivity among natal sources defines the demographic and genetic boundaries of a population. Yet, the role that immigration of hatchery-produced adults may play in altering population dynamics and fitness of natural populations remains largely unquantified. Quantifying, whether natural populations are self-sustaining, functions as sources (population growth rate in the absence of dispersal, λ>1), or as sinks (λ<1) can be obscured by an inability to identify immigrants. In this study we use a new isotopic approach to demonstrate that a natural spawning population of Chinook salmon, (Oncorhynchus tshawytscha) considered relatively healthy, represents a sink population when the contribution of hatchery immigrants is taken into consideration. We retrieved sulfur isotopes (34S/32S, referred to as δ34S) in adult Chinook salmon otoliths (ear bones) that were deposited during their early life history as juveniles to determine whether individuals were produced in hatcheries or naturally in rivers. Our results show that only 10.3% (CI = 5.5 to 18.1%) of adults spawning in the river had otolith δ34S values less than 8.5‰, which is characteristic of naturally produced salmon. When considering the total return to the watershed (total fish in river and hatchery), we estimate that 90.7 to 99.3% (CI) of returning adults were produced in a hatchery (best estimate = 95.9%). When population growth rate of the natural population was modeled to account for the contribution of previously unidentified hatchery immigrants, we found that hatchery-produced fish caused the false appearance of positive population growth. These findings highlight the potential dangers in ignoring source-sink dynamics in recovering natural populations, and question the extent to which declines in natural salmon populations are undetected by monitoring programs

Fortune Favours the Bold: An Agent-Based Model Reveals Adaptive Advantages of Overconfidence in War

Overconfidence has long been considered a cause of war. Like other decision-making biases, overconfidence seems detrimental because it increases the frequency and costs of fighting. However, evolutionary biologists have proposed that overconfidence may also confer adaptive advantages: increasing ambition, resolve, persistence, bluffing opponents, and winning net payoffs from risky opportunities despite occasional failures. We report the results of an agent-based model of inter-state conflict, which allows us to evaluate the performance of different strategies in competition with each other. Counter-intuitively, we find that overconfident states predominate in the population at the expense of unbiased or underconfident states. Overconfident states win because: (1) they are more likely to accumulate resources from frequent attempts at conquest; (2) they are more likely to gang up on weak states, forcing victims to split their defences; and (3) when the decision threshold for attacking requires an overwhelming asymmetry of power, unbiased and underconfident states shirk many conflicts they are actually likely to win. These “adaptive advantages” of overconfidence may, via selection effects, learning, or evolved psychology, have spread and become entrenched among modern states, organizations and decision-makers. This would help to explain the frequent association of overconfidence and war, even if it no longer brings benefits today

Measurements of Higgs bosons decaying to bottom quarks from vector boson fusion production with the ATLAS experiment at √=13TeV

The paper presents a measurement of the Standard Model Higgs Boson decaying to b-quark pairs in the vector boson fusion (VBF) production mode. A sample corresponding to 126 fb−1 of s√=13TeV proton–proton collision data, collected with the ATLAS experiment at the Large Hadron Collider, is analyzed utilizing an adversarial neural network for event classification. The signal strength, defined as the ratio of the measured signal yield to that predicted by the Standard Model for VBF Higgs production, is measured to be 0.95+0.38−0.36 , corresponding to an observed (expected) significance of 2.6 (2.8) standard deviations from the background only hypothesis. The results are additionally combined with an analysis of Higgs bosons decaying to b-quarks, produced via VBF in association with a photon

Muon reconstruction and identification efficiency in ATLAS using the full Run 2 pp collision data set at \sqrt{s}=13 TeV

This article documents the muon reconstruction and identification efficiency obtained by the ATLAS experiment for 139 \hbox {fb}^{-1} of pp collision data at \sqrt{s}=13 TeV collected between 2015 and 2018 during Run 2 of the LHC. The increased instantaneous luminosity delivered by the LHC over this period required a reoptimisation of the criteria for the identification of prompt muons. Improved and newly developed algorithms were deployed to preserve high muon identification efficiency with a low misidentification rate and good momentum resolution. The availability of large samples of Z\rightarrow \mu \mu and J/\psi \rightarrow \mu \mu decays, and the minimisation of systematic uncertainties, allows the efficiencies of criteria for muon identification, primary vertex association, and isolation to be measured with an accuracy at the per-mille level in the bulk of the phase space, and up to the percent level in complex kinematic configurations. Excellent performance is achieved over a range of transverse momenta from 3 GeV to several hundred GeV, and across the full muon detector acceptance of |\eta |<2.7

Dijet Resonance Search with Weak Supervision Using root S=13 TeV pp Collisions in the ATLAS Detector

This Letter describes a search for narrowly resonant new physics using a machine-learning anomaly detection procedure that does not rely on signal simulations for developing the analysis selection. Weakly supervised learning is used to train classifiers directly on data to enhance potential signals. The targeted topology is dijet events and the features used for machine learning are the masses of the two jets. The resulting analysis is essentially a three-dimensional search A → BC, for mA ∼ OðTeVÞ, mB; mC ∼ Oð100 GeVÞ and B, C are reconstructed as large-radius jets, without paying a penalty associated with a large trials factor in the scan of the masses of the two jets. The full run 2 ffiffi s p ¼ 13 TeV pp collision dataset of 139 fb−1 recorded by the ATLAS detector at the Large Hadron Collider is used for the search. There is no significant evidence of a localized excess in the dijet invariant mass spectrum between 1.8 and 8.2 TeV. Cross-section limits for narrow-width A, B, and C particles vary with mA, mB, and mC. For example, when mA ¼ 3 TeV and mB ≳ 200 GeV, a production cross section between 1 and 5 fb is excluded at 95% confidence level, depending on mC. For certain masses, these limits are up to 10 times more sensitive than those obtained by the inclusive dijet search. These results are complementary to the dedicated searches for the case that B and C are standard model boson