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Institution

York University

EducationToronto, Ontario, Canada
About: York University is a education organization based out in Toronto, Ontario, Canada. It is known for research contribution in the topics: Population & Politics. The organization has 18899 authors who have published 43357 publications receiving 1568560 citations.


Papers
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Journal ArticleDOI
Georges Aad1, T. Abajyan2, Brad Abbott3, Jalal Abdallah4  +2885 moreInstitutions (169)
TL;DR: In this article, the electron reconstruction and identification efficiencies of the ATLAS detector at the LHC have been evaluated using proton-proton collision data collected in 2011 at TeV and corresponding to an integrated luminosity of 4.7 fb.
Abstract: Many of the interesting physics processes to be measured at the LHC have a signature involving one or more isolated electrons. The electron reconstruction and identification efficiencies of the ATLAS detector at the LHC have been evaluated using proton-proton collision data collected in 2011 at TeV and corresponding to an integrated luminosity of 4.7 fb. Tag-and-probe methods using events with leptonic decays of and bosons and mesons are employed to benchmark these performance parameters. The combination of all measurements results in identification efficiencies determined with an accuracy at the few per mil level for electron transverse energy greater than 30 GeV.

302 citations

Journal ArticleDOI
TL;DR: An extensive set of Monte Carlo simulations to examine different methods of variance estimation when using a weighted Cox proportional hazards model to estimate the effect of treatment found that the use of a bootstrap estimator resulted in approximately correct estimates of standard errors and confidence intervals with the correct coverage rates.
Abstract: Propensity score methods are used to reduce the effects of observed confounding when using observational data to estimate the effects of treatments or exposures. A popular method of using the propensity score is inverse probability of treatment weighting (IPTW). When using this method, a weight is calculated for each subject that is equal to the inverse of the probability of receiving the treatment that was actually received. These weights are then incorporated into the analyses to minimize the effects of observed confounding. Previous research has found that these methods result in unbiased estimation when estimating the effect of treatment on survival outcomes. However, conventional methods of variance estimation were shown to result in biased estimates of standard error. In this study, we conducted an extensive set of Monte Carlo simulations to examine different methods of variance estimation when using a weighted Cox proportional hazards model to estimate the effect of treatment. We considered three variance estimation methods: (i) a naive model-based variance estimator; (ii) a robust sandwich-type variance estimator; and (iii) a bootstrap variance estimator. We considered estimation of both the average treatment effect and the average treatment effect in the treated. We found that the use of a bootstrap estimator resulted in approximately correct estimates of standard errors and confidence intervals with the correct coverage rates. The other estimators resulted in biased estimates of standard errors and confidence intervals with incorrect coverage rates. Our simulations were informed by a case study examining the effect of statin prescribing on mortality. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

302 citations

Journal ArticleDOI
TL;DR: The ubiquitous evidence of specific cell and circuit properties underlying synchronized activity across theta, alpha, beta and gamma frequency bands is surveyed and shows that their activation likely implements gain control, context-dependent gating and state-specific integration of synaptic inputs, giving rise to the dynamic circuit motifs hypothesis of synchronized activation states.
Abstract: Brain circuitry processes information by rapidly and selectively engaging functional neuronal networks. The dynamic formation of networks is often evident in rhythmically synchronized neuronal activity and tightly correlates with perceptual, cognitive and motor performances. But how synchronized neuronal activity contributes to network formation and how it relates to the computation of behaviorally relevant information has remained difficult to discern. Here we structure recent empirical advances that link synchronized activity to the activation of so-called dynamic circuit motifs. These motifs explicitly relate (1) synaptic and cellular properties of circuits to (2) identified timescales of rhythmic activation and to (3) canonical circuit computations implemented by rhythmically synchronized circuits. We survey the ubiquitous evidence of specific cell and circuit properties underlying synchronized activity across theta, alpha, beta and gamma frequency bands and show that their activation likely implements gain control, context-dependent gating and state-specific integration of synaptic inputs. This evidence gives rise to the dynamic circuit motifs hypothesis of synchronized activation states, with its core assertion that activation states are linked to uniquely identifiable local circuit structures that are recruited during the formation of functional networks to perform specific computational operations.

301 citations

Journal ArticleDOI
TL;DR: In this article, the authors investigate the stakeholder theory of capital structure from the perspective of a firm's relations with its employees and find that firms that treat their employees fairly (as measured by high employee friendly ratings) maintain low debt ratios.

301 citations

Proceedings ArticleDOI
15 Dec 2008
TL;DR: This paper shows that the helpfulness of a review depends on three important factors: the reviewerpsilas expertise, the writing style of the review, and the timeliness of thereview, and presents a nonlinear regression model for helpfulness prediction.
Abstract: Online reviews provide a valuable resource for potential customers to make purchase decisions. However, the sheer volume of available reviews as well as the large variations in the review quality present a big impediment to the effective use of the reviews, as the most helpful reviews may be buried in the large amount of low quality reviews. The goal of this paper is to develop models and algorithms for predicting the helpfulness of reviews, which provides the basis for discovering the most helpful reviews for given products. We first show that the helpfulness of a review depends on three important factors: the reviewerpsilas expertise, the writing style of the review, and the timeliness of the review. Based on the analysis of those factors, we present a nonlinear regression model for helpfulness prediction. Our empirical study on the IMDB movie reviews dataset demonstrates that the proposed approach is highly effective.

301 citations


Authors

Showing all 19301 results

NameH-indexPapersCitations
Dan R. Littman157426107164
Martin J. Blaser147820104104
Aaron Dominguez1471968113224
Gregory R Snow1471704115677
Joseph E. LeDoux13947891500
Kenneth Bloom1381958110129
Osamu Jinnouchi13588586104
Steven A. Narod13497084638
David H. Barlow13378672730
Elliott Cheu133121991305
Roger Moore132167798402
Wendy Taylor131125289457
Stephen P. Jackson13137276148
Flera Rizatdinova130124289525
Sudhir Malik130166998522
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023180
2022528
20212,676
20202,857
20192,426
20182,137