Institution
University of Ioannina
Education•Ioannina, Greece•
About: University of Ioannina is a education organization based out in Ioannina, Greece. It is known for research contribution in the topics: Population & Large Hadron Collider. The organization has 7654 authors who have published 20594 publications receiving 671560 citations. The organization is also known as: Panepistimio Ioanninon.
Papers published on a yearly basis
Papers
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TL;DR: The aim is to identify known methods for estimation of the between‐study variance and its corresponding uncertainty, and to summarise the simulation and empirical evidence that compares them and recommend the Q‐profile method and the alternative approach based on a ‘generalised Cochran between‐ study variance statistic’.
Abstract: Meta-analyses are typically used to estimate the overall/mean of an outcome of interest. However, inference about between-study variability, which is typically modelled using a between-study variance parameter, is usually an additional aim. The DerSimonian and Laird method, currently widely used by default to estimate the between-study variance, has been long challenged. Our aim is to identify known methods for estimation of the between-study variance and its corresponding uncertainty, and to summarise the simulation and empirical evidence that compares them. We identified 16 estimators for the between-study variance, seven methods to calculate confidence intervals, and several comparative studies. Simulation studies suggest that for both dichotomous and continuous data the estimator proposed by Paule and Mandel and for continuous data the restricted maximum likelihood estimator are better alternatives to estimate the between-study variance. Based on the scenarios and results presented in the published studies, we recommend the Q-profile method and the alternative approach based on a 'generalised Cochran between-study variance statistic' to compute corresponding confidence intervals around the resulting estimates. Our recommendations are based on a qualitative evaluation of the existing literature and expert consensus. Evidence-based recommendations require an extensive simulation study where all methods would be compared under the same scenarios.
828 citations
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TL;DR: Evidence does not support the argument that vitamin D only supplementation increases bone mineral density or reduces the risk of fractures or falls in older people, and highly convincing evidence of a clear role of vitamin D does not exist for any outcome, but associations with a selection of outcomes are probable.
Abstract: Objective To evaluate the breadth, validity, and presence of biases of the associations of vitamin D with diverse outcomes.
791 citations
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29 Mar 2012
TL;DR: In this article, the authors reported results from searches for the standard model Higgs boson in proton-proton collisions at square root(s) = 7 TeV in five decay modes: gamma pair, b-quark pair, tau lepton pair, W pair, and Z pair.
Abstract: Combined results are reported from searches for the standard model Higgs boson in proton-proton collisions at sqrt(s)=7 TeV in five Higgs boson decay modes: gamma pair, b-quark pair, tau lepton pair, W pair, and Z pair. The explored Higgs boson mass range is 110-600 GeV. The analysed data correspond to an integrated luminosity of 4.6-4.8 inverse femtobarns. The expected excluded mass range in the absence of the standard model Higgs boson is 118-543 GeV at 95% CL. The observed results exclude the standard model Higgs boson in the mass range 127-600 GeV at 95% CL, and in the mass range 129-525 GeV at 99% CL. An excess of events above the expected standard model background is observed at the low end of the explored mass range making the observed limits weaker than expected in the absence of a signal. The largest excess, with a local significance of 3.1 sigma, is observed for a Higgs boson mass hypothesis of 124 GeV. The global significance of observing an excess with a local significance greater than 3.1 sigma anywhere in the search range 110-600 (110-145) GeV is estimated to be 1.5 sigma (2.1 sigma). More data are required to ascertain the origin of this excess.
786 citations
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TL;DR: It was from here that "Bayesian" ideas first spread through the mathematical world, as Bayes's own article was ignored until 1780 and played no important role in scientific debate until the 20th century.
Abstract: The influence of this Thomas Bayes' work was immense. It was from here that "Bayesian" ideas first spread through the mathematical world, as Bayes's own article was ignored until 1780 and played no important role in scientific debate until the 20th century. It was also this article of Laplace's that introduced the mathematical techniques for the asymptotic analysis of posterior distributions that are still employed today. And it was here that the earliest example of optimum estimation can be found, the derivation and characterization of an estimator that minimized a particular measure of posterior expected loss. After more than two centuries, we mathematicians, statisticians cannot only recognize our roots in this masterpiece of our science, we can still learn from it.
774 citations
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University of Ottawa1, University of Ioannina2, University of Bern3, Centers for Disease Control and Prevention4, PLOS5, University of Bristol6, Ottawa Hospital Research Institute7, University of Texas Health Science Center at Houston8, University of Western Ontario9, Erasmus University Rotterdam10, Cancer Care Ontario11, McGill University12, Harvard University13
TL;DR: The STREGA recommendations are presented, which are aimed at improving the reporting of genetic association studies and are designed to improve the quality of studies.
Abstract: Making sense of rapidly evolving evidence on genetic associations is crucial to making genuine advances in human genomics and the eventual integration of this information in the practice of medicine and public health. Assessment of the strengths and weaknesses of this evidence, and hence the ability to synthesize it, has been limited by inadequate reporting of results. The STrengthening the REporting of Genetic Association studies (STREGA) initiative builds on the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement and provides additions to 12 of the 22 items on the STROBE checklist. The additions concern population stratification, genotyping errors, modelling haplotype variation, Hardy-Weinberg equilibrium, replication, selection of participants, rationale for choice of genes and variants, treatment effects in studying quantitative traits, statistical methods, relatedness, reporting of descriptive and outcome data, and the volume of data issues that are important to consider in genetic association studies. The STREGA recommendations do not prescribe or dictate how a genetic association study should be designed but seek to enhance the transparency of its reporting, regardless of choices made during design, conduct, or analysis.
766 citations
Authors
Showing all 7724 results
Name | H-index | Papers | Citations |
---|---|---|---|
John P. A. Ioannidis | 185 | 1311 | 193612 |
Kay-Tee Khaw | 174 | 1389 | 138782 |
Elio Riboli | 158 | 1136 | 110499 |
Mercouri G. Kanatzidis | 152 | 1854 | 113022 |
Dimitrios Trichopoulos | 135 | 818 | 84992 |
Gyorgy Vesztergombi | 133 | 1444 | 94821 |
Niki Saoulidou | 132 | 1065 | 81154 |
Apostolos Panagiotou | 132 | 1370 | 88647 |
Ioannis Evangelou | 131 | 1225 | 82178 |
Ioannis Papadopoulos | 129 | 1201 | 85576 |
Nikolaos Manthos | 129 | 1256 | 81865 |
Panagiotis Kokkas | 128 | 1234 | 81051 |
Costas Foudas | 128 | 1112 | 83048 |
Zoltan Szillasi | 128 | 1214 | 84392 |
Matthias Schröder | 126 | 1421 | 82990 |