414 research outputs found
Sufficient Covariate, Propensity Variable and Doubly Robust Estimation
Statistical causal inference from observational studies often requires
adjustment for a possibly multi-dimensional variable, where dimension reduction
is crucial. The propensity score, first introduced by Rosenbaum and Rubin, is a
popular approach to such reduction. We address causal inference within Dawid's
decision-theoretic framework, where it is essential to pay attention to
sufficient covariates and their properties. We examine the role of a propensity
variable in a normal linear model. We investigate both population-based and
sample-based linear regressions, with adjustments for a multivariate covariate
and for a propensity variable. In addition, we study the augmented inverse
probability weighted estimator, involving a combination of a response model and
a propensity model. In a linear regression with homoscedasticity, a propensity
variable is proved to provide the same estimated causal effect as multivariate
adjustment. An estimated propensity variable may, but need not, yield better
precision than the true propensity variable. The augmented inverse probability
weighted estimator is doubly robust and can improve precision if the propensity
model is correctly specified
Global Search for New Physics with 2.0/fb at CDF
Data collected in Run II of the Fermilab Tevatron are searched for
indications of new electroweak-scale physics. Rather than focusing on
particular new physics scenarios, CDF data are analyzed for discrepancies with
the standard model prediction. A model-independent approach (Vista) considers
gross features of the data, and is sensitive to new large cross-section
physics. Further sensitivity to new physics is provided by two additional
algorithms: a Bump Hunter searches invariant mass distributions for "bumps"
that could indicate resonant production of new particles; and the Sleuth
procedure scans for data excesses at large summed transverse momentum. This
combined global search for new physics in 2.0/fb of ppbar collisions at
sqrt(s)=1.96 TeV reveals no indication of physics beyond the standard model.Comment: 8 pages, 7 figures. Final version which appeared in Physical Review D
Rapid Communication
Observation of Orbitally Excited B_s Mesons
We report the first observation of two narrow resonances consistent with
states of orbitally excited (L=1) B_s mesons using 1 fb^{-1} of ppbar
collisions at sqrt{s} = 1.96 TeV collected with the CDF II detector at the
Fermilab Tevatron. We use two-body decays into K^- and B^+ mesons reconstructed
as B^+ \to J/\psi K^+, J/\psi \to \mu^+ \mu^- or B^+ \to \bar{D}^0 \pi^+,
\bar{D}^0 \to K^+ \pi^-. We deduce the masses of the two states to be m(B_{s1})
= 5829.4 +- 0.7 MeV/c^2 and m(B_{s2}^*) = 5839.7 +- 0.7 MeV/c^2.Comment: Version accepted and published by Phys. Rev. Let
Shrinking a large dataset to identify variables associated with increased risk of Plasmodium falciparum infection in Western Kenya
Large datasets are often not amenable to analysis using traditional single-step approaches. Here, our general objective was to apply imputation techniques, principal component analysis (PCA), elastic net and generalized linear models to a large dataset in a systematic approach to extract the most meaningful predictors for a health outcome. We extracted predictors for Plasmodium falciparum infection, from a large covariate dataset while facing limited numbers of observations, using data from the People, Animals, and their Zoonoses (PAZ) project to demonstrate these techniques: data collected from 415 homesteads in western Kenya, contained over 1500 variables that describe the health, environment, and social factors of the humans, livestock, and the homesteads in which they reside. The wide, sparse dataset was simplified to 42 predictors of P. falciparum malaria infection and wealth rankings were produced for all homesteads. The 42 predictors make biological sense and are supported by previous studies. This systematic data-mining approach we used would make many large datasets more manageable and informative for decision-making processes and health policy prioritization
Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set
We report a measurement of the bottom-strange meson mixing phase \beta_s
using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays
in which the quark-flavor content of the bottom-strange meson is identified at
production. This measurement uses the full data set of proton-antiproton
collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment
at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity.
We report confidence regions in the two-dimensional space of \beta_s and the
B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2,
-1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in
agreement with the standard model expectation. Assuming the standard model
value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +-
0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +-
0.009 (syst) ps, which are consistent and competitive with determinations by
other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012
Search for direct production of charginos and neutralinos in events with three leptons and missing transverse momentum in √s = 7 TeV pp collisions with the ATLAS detector
A search for the direct production of charginos and neutralinos in final states with three electrons or muons and missing transverse momentum is presented. The analysis is based on 4.7 fb−1 of proton–proton collision data delivered by the Large Hadron Collider and recorded with the ATLAS detector. Observations are consistent with Standard Model expectations in three signal regions that are either depleted or enriched in Z-boson decays. Upper limits at 95% confidence level are set in R-parity conserving phenomenological minimal supersymmetric models and in simplified models, significantly extending previous results
Jet size dependence of single jet suppression in lead-lead collisions at sqrt(s(NN)) = 2.76 TeV with the ATLAS detector at the LHC
Measurements of inclusive jet suppression in heavy ion collisions at the LHC
provide direct sensitivity to the physics of jet quenching. In a sample of
lead-lead collisions at sqrt(s) = 2.76 TeV corresponding to an integrated
luminosity of approximately 7 inverse microbarns, ATLAS has measured jets with
a calorimeter over the pseudorapidity interval |eta| < 2.1 and over the
transverse momentum range 38 < pT < 210 GeV. Jets were reconstructed using the
anti-kt algorithm with values for the distance parameter that determines the
nominal jet radius of R = 0.2, 0.3, 0.4 and 0.5. The centrality dependence of
the jet yield is characterized by the jet "central-to-peripheral ratio," Rcp.
Jet production is found to be suppressed by approximately a factor of two in
the 10% most central collisions relative to peripheral collisions. Rcp varies
smoothly with centrality as characterized by the number of participating
nucleons. The observed suppression is only weakly dependent on jet radius and
transverse momentum. These results provide the first direct measurement of
inclusive jet suppression in heavy ion collisions and complement previous
measurements of dijet transverse energy imbalance at the LHC.Comment: 15 pages plus author list (30 pages total), 8 figures, 2 tables,
submitted to Physics Letters B. All figures including auxiliary figures are
available at
http://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/HION-2011-02
Drug and alcohol use among people living with HIV in care in the United States by geographic region
Substance use in the U.S. varies by geographic region. Opioid prescribing practices and marijuana, heroin, and methamphetamine availability are evolving differently across regions. We examined self-reported substance use among people living with HIV (PLWH) in care at seven sites from 2017–2019 to understand current regional substance use patterns. We calculated the percentage and standardized percentage of PLWH reporting current drug use and at-risk and binge alcohol use by U.S. Census Bureau geographic region and examined associations in adjusted logistic regression analyses. Among 7,686 PLWH, marijuana use was the most prevalent drug (30%), followed by methamphetamine/crystal (8%), cocaine/crack (7%), and illicit opioids (3%). One-third reported binge alcohol use (32%). Differences in percent of current use by region were seen for marijuana (24–41%) and methamphetamine/crystal (2–15%), with more use in the West and Northeast, and binge alcohol use (26–40%). In adjusted analyses, PLWH in the Midwest were significantly less likely to use methamphetamine/crystal (aOR: 0.13;0.06–0.25) or illicit opioids (aOR:0.16;0.05–0.53), and PLWH in the Northeast were more likely to use cocaine/crack (aOR:1.59;1.16–2.17), compared to PLWH in the West. Understanding differences in substance use patterns in the current era, as policies continue to evolve, will enable more targeted interventions in clinical settings among PLWH
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