Search results for "event"

showing 10 items of 4065 documents

The Psychological Science Accelerator’s COVID-19 rapid-response dataset

2023

Funder: Amazon Web Services (AWS) Imagine Grant

Statistics and Probability223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore copingBF Psychology230 Affective NeuroscienceHealth Behaviorand demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73Message framingDiseasesLibrary and Information Sciences:Ciências Sociais::Psicologia [Domínio/Área Científica]geographical and cultural context characterizationHV Social pathology. Social and public welfare. CriminologypandemiatEducationa general questionnaire examining health prevention behaviors and COVID-19 experienceddc:150SDG 3 - Good Health and Well-beingRA0421 Public health. Hygiene. Preventive MedicineSurveys and QuestionnairesAdaptation PsychologicalyleiskartoituksetHumansPendienteHealth behaviorsPandemicsframingBehaviour Change and Well-beingEmotion regulationSelf-determination messagingand self-determination across a diverseCOVID-19kansainvälinen vertailuResearch dataComputer Science Applicationswhich can be merged with other time-sampled or geographic data.cognitive reappraisalsglobal sample obtained at the onset of the COVID-19 pandemicterveyskäyttäytyminenIn response to the COVID-19 pandemic/dk/atira/pure/sustainabledevelopmentgoals/good_health_and_well_beingand autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental studyStatistics Probability and UncertaintyPeople’s healthtutkimusaineistosurvey-tutkimusDatasetInformation Systemsthe Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing
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Marginal hazard ratio estimates in joint frailty models for heart failure trials

2019

Abstract This work is motivated by clinical trials in chronic heart failure disease, where treatment has effects both on morbidity (assessed as recurrent non‐fatal hospitalisations) and on mortality (assessed as cardiovascular death, CV death). Recently, a joint frailty proportional hazards model has been proposed for these kind of efficacy outcomes to account for a potential association between the risk rates for hospital admissions and CV death. However, more often clinical trial results are presented by treatment effect estimates that have been derived from marginal proportional hazards models, that is, a Cox model for mortality and an Andersen–Gill model for recurrent hospitalisations. …

Statistics and ProbabilityBiometryleast false parameterDiseasejoint frailty modelRisk AssessmentStudy durationCardiovascular deathunexplained heterogeneitymedicineHumansTreatment effectComplex Regression ModelsProportional Hazards ModelsHeart FailureClinical Trials as TopicProportional hazards modelbusiness.industryheart failure trialsHazard ratioGeneral Medicinemedicine.diseaseClinical trialrecurrent eventsHeart failureAsymptomatic DiseasesStatistics Probability and UncertaintybusinessDemographyResearch PaperBiometrical Journal. Biometrische Zeitschrift
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The linear birth and death process under the influence of independently occurring disasters

1989

A population developing according to a time homogeneous linear birth and death process is subjected to an independently occurring random sequence of disasters. Using an embedded Galton-Watson process with random environments explicit results about the probability of extinction and the asymptotic behavior of the process are obtained.

Statistics and ProbabilityBirth and death processeducation.field_of_studyExtinctionPopulationRandom sequenceBirth–death processMathematics::ProbabilityHomogeneousStatisticsQuantitative Biology::Populations and EvolutionRandom eventStatistics Probability and UncertaintyeducationAnalysisDemographyMathematicsProbability Theory and Related Fields
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Opportunities and challenges of combined effect measures based on prioritized outcomes

2013

Many authors have proposed different approaches to combine multiple endpoints in a univariate outcome measure in the literature. In case of binary or time-to-event variables, composite endpoints, which combine several event types within a single event or time-to-first-event analysis are often used to assess the overall treatment effect. A main drawback of this approach is that the interpretation of the composite effect can be difficult as a negative effect in one component can be masked by a positive effect in another. Recently, some authors proposed more general approaches based on a priority ranking of outcomes, which moreover allow to combine outcome variables of different scale levels. …

Statistics and ProbabilityClinical Trials as TopicEpidemiologyUnivariatecomputer.software_genreOutcome (game theory)Treatment OutcomeRankingScale (social sciences)Component (UML)Outcome Assessment Health CareMultiple comparisons problemHumansComputer SimulationData miningcomputerProportional Hazards ModelsMathematicsStatistical hypothesis testingEvent (probability theory)Statistics in Medicine
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Sequential Monte Carlo methods in Bayesian joint models for longitudinal and time-to-event data

2020

The statistical analysis of the information generated by medical follow-up is a very important challenge in the field of personalized medicine. As the evolutionary course of a patient's disease progresses, his/her medical follow-up generates more and more information that should be processed immediately in order to review and update his/her prognosis and treatment. Hence, we focus on this update process through sequential inference methods for joint models of longitudinal and time-to-event data from a Bayesian perspective. More specifically, we propose the use of sequential Monte Carlo (SMC) methods for static parameter joint models with the intention of reducing computational time in each…

Statistics and ProbabilityComputer sciencebusiness.industryBayesian probabilitySequential monte carlo methodsMachine learningcomputer.software_genre01 natural sciencesField (computer science)010104 statistics & probability03 medical and health sciences0302 clinical medicineEvent data030220 oncology & carcinogenesisStatistical analysisPersonalized medicineArtificial intelligence0101 mathematicsStatistics Probability and UncertaintybusinessJoint (audio engineering)CartographycomputerStatistical Modelling
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Mixed Non-Parametric and Parametric Estimation Techniques in R Package etasFLP for Earthquakes’ Description

2017

etasFLP is an R package which fits an epidemic type aftershock sequence (ETAS) model to an earthquake catalog; non-parametric background seismicity can be estimated through a forward predictive likelihood approach, while parametric components of triggered seismicity are estimated through maximum likelihood; estimation steps are alternated until convergence is obtained and for each event the probability of being a background event is estimated. The package includes options which allow its wide use. Methods for plot, summary and profile are defined for the main output class object. The paper provides examples of the package's use with description of the underlying R and Fortran routines.

Statistics and ProbabilityEarthquakeComputer scienceFortranFortranInduced seismicity010502 geochemistry & geophysicscomputer.software_genre01 natural sciencesPlot (graphics)Point processPhysics::GeophysicsPoint proce010104 statistics & probabilityetasFLP; R; Fortran; point process; ETAS; earthquakesETAS0101 mathematicsearthquakeslcsh:Statisticslcsh:HA1-4737AftershockEtasFLPpoint process0105 earth and related environmental sciencesEvent (probability theory)Parametric statisticscomputer.programming_languageNonparametric statisticsRetasFLP R Fortran point process ETAS earthquakes.Data miningStatistics Probability and UncertaintySettore SECS-S/01 - StatisticacomputerAlgorithmSoftware
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Rare events and scaling properties in field-induced anomalous dynamics

2012

We show that, in a broad class of continuous time random walks (CTRW), a small external field can turn diffusion from standard into anomalous. We illustrate our findings in a CTRW with trapping, a prototype of subdiffusion in disordered and glassy materials, and in the L\'evy walk process, which describes superdiffusion within inhomogeneous media. For both models, in the presence of an external field, rare events induce a singular behavior in the originally Gaussian displacements distribution, giving rise to power-law tails. Remarkably, in the subdiffusive CTRW, the combined effect of highly fluctuating waiting times and of a drift yields a non-Gaussian distribution characterized by long sp…

Statistics and ProbabilityField (physics)GaussianFOS: Physical sciencesQuantitative Biology::Cell Behaviorsymbols.namesaketransport processes/heat transfer (theory). diffusionRare eventsstochastic particle dynamics (theory)Statistical physicsDiffusion (business)ScalingPhysicsdiffusiondriven diffusive systems (theory)Statistical and Nonlinear PhysicsDisordered Systems and Neural Networks (cond-mat.dis-nn)Condensed Matter - Disordered Systems and Neural NetworksRandom walkDistribution (mathematics)Lévy flighttransport processes/heat transfer (theory)symbolsdiffusion; stochastic particle dynamics (theory); driven diffusive systems (theory); transport processes/heat transfer (theory)Statistics Probability and UncertaintyStatistical and Nonlinear PhysicJournal of Statistical Mechanics: Theory and Experiment
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A weighted combined effect measure for the analysis of a composite time-to-first-event endpoint with components of different clinical relevance

2018

Composite endpoints combine several events within a single variable, which increases the number of expected events and is thereby meant to increase the power. However, the interpretation of results can be difficult as the observed effect for the composite does not necessarily reflect the effects for the components, which may be of different magnitude or even point in adverse directions. Moreover, in clinical applications, the event types are often of different clinical relevance, which also complicates the interpretation of the composite effect. The common effect measure for composite endpoints is the all-cause hazard ratio, which gives equal weight to all events irrespective of their type …

Statistics and ProbabilityHazard (logic)EpidemiologyEndpoint Determination01 natural sciencesMeasure (mathematics)WIN RATIO010104 statistics & probability03 medical and health sciences0302 clinical medicineResamplingStatisticstime-to-eventHumansComputer Simulation030212 general & internal medicinerelevance weighting0101 mathematicsParametric statisticsEvent (probability theory)MathematicsProportional Hazards Modelsclinical trialsHazard ratiocomposite endpointWeightingPRIORITIZED OUTCOMESTRIALSData Interpretation StatisticalMULTISTATE MODELSINFERENCENull hypothesisMonte Carlo MethodStatistics in Medicine
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Using Statistical and Computer Models to Quantify Volcanic Hazards

2009

Risk assessment of rare natural hazards, such as large volcanic block and ash or pyroclastic flows, is addressed. Assessment is approached through a combination of computer modeling, statistical modeling, and extreme-event probability computation. A computer model of the natural hazard is used to provide the needed extrapolation to unseen parts of the hazard space. Statistical modeling of the available data is needed to determine the initializing distribution for exercising the computer model. In dealing with rare events, direct simulations involving the computer model are prohibitively expensive. The solution instead requires a combination of adaptive design of computer model approximation…

Statistics and ProbabilityHazard (logic)Risk analysisVolcanic hazardsComputer scienceApplied MathematicsComputationInitializationStatistical modelcomputer.software_genreModeling and SimulationNatural hazardRare eventsData miningcomputerTechnometrics
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PROBABILISTIC QUANTIFICATION OF HAZARDS: A METHODOLOGY USING SMALL ENSEMBLES OF PHYSICS-BASED SIMULATIONS AND STATISTICAL SURROGATES

2015

This paper presents a novel approach to assessing the hazard threat to a locale due to a large volcanic avalanche. The methodology combines: (i) mathematical modeling of volcanic mass flows; (ii) field data of avalanche frequency, volume, and runout; (iii) large-scale numerical simulations of flow events; (iv) use of statistical methods to minimize computational costs, and to capture unlikely events; (v) calculation of the probability of a catastrophic flow event over the next T years at a location of interest; and (vi) innovative computational methodology to implement these methods. This unified presentation collects elements that have been separately developed, and incorporates new contri…

Statistics and ProbabilityHazard (logic)Volcanic hazardsgeographyControl and Optimizationgeography.geographical_feature_categoryProcess (engineering)Probabilistic logicHazard analysiscomputer.software_genreFlow (mathematics)VolcanoModeling and SimulationEconometricsDiscrete Mathematics and CombinatoricsEnvironmental scienceData miningcomputerEvent (probability theory)International Journal for Uncertainty Quantification
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