Search results for "hypothesis test"

showing 10 items of 127 documents

A validity and reliability study of Conditional Entropy Measures of Pulse Rate Variability

2019

In this work, we present the feasibility to use a simpler methodological approach for the assessment of the short-term complexity of Heart Rate Variability (HRV). Specifically, we propose to exploit Pulse Rate Variability (PRV) recorded through photoplethysmography in place of HRV measured from the ECG, and to compute complexity via a linear Gaussian approximation in place of the standard model-free methods (e.g., nearest neighbor entropy estimates) usually applied to HRV. Linear PRV-based and model-free HRV-based complexity measures were compared via statistical tests, correlation analysis and Bland-Altman plots, demonstrating an overall good agreement. These results support the applicabil…

020205 medical informaticsComputer scienceEntropy0206 medical engineeringValidity02 engineering and technologySettore ING-INF/01 - ElettronicaElectrocardiographyPulse Rate Variability (PRV)Heart RatePhotoplethysmogram0202 electrical engineering electronic engineering information engineeringHumansEntropy (information theory)Heart rate variabilityEntropy (energy dispersal)Time seriesPhotoplethysmographyEntropy (arrow of time)Statistical hypothesis testingConditional entropyEntropy (statistical thermodynamics)Reproducibility of ResultsHeart Rate Variability (HRV)020601 biomedical engineeringSettore ING-INF/06 - Bioingegneria Elettronica E InformaticacomplexityAlgorithmEntropy (order and disorder)2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
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Location-Aware MAC Scheduling in Industrial-Like Environment

2018

We consider an environment strongly affected by the presence of metallic objects, that can be considered representative of an indoor industrial environment with metal obstacles. This scenario is a very harsh environment where radio communication has notorious difficulties, as metallic objects create a strong blockage component and surfaces are highly reflective. In this environment, we investigate how to dynamically allocate MAC resources in time to static and mobile users based on context awareness extracted from a legacy WiFi positioning system. In order to address this problem, we integrate our WiFi ranging and positioning system in the WiSHFUL architecture and then define a hypothesis t…

0209 industrial biotechnologyPositioning systemSettore ING-INF/03 - TelecomunicazioniComputer scienceDistributed computingContext awareness020206 networking & telecommunicationsContext (language use)Ranging02 engineering and technologyNon-line-of-sight propagation020901 industrial engineering & automationIndoor localization systemComponent (UML)MAC scheduler0202 electrical engineering electronic engineering information engineeringContext awarenessArchitectureStatistical hypothesis testing
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Reducing sample size in experiments with animals: historical controls and related strategies

2015

Reducing the number of animal subjects used in biomedical experiments is desirable for ethical and practical reasons. Previous reviews of the benefits of reducing sample sizes have focused on improving experimental designs and methods of statistical analysis, but reducing the size of control groups has been considered rarely. We discuss how the number of current control animals can be reduced, without loss of statistical power, by incorporating information from historical controls, i.e. subjects used as controls in similar previous experiments. Using example data from published reports, we describe how to incorporate information from historical controls under a range of assumptions that mig…

0301 basic medicineComputer scienceDesign of experimentsControl (management)Control subjects01 natural sciencesGeneral Biochemistry Genetics and Molecular BiologyStatistical power010104 statistics & probability03 medical and health sciences030104 developmental biologySample size determinationStatisticsRange (statistics)Statistical analysis0101 mathematicsGeneral Agricultural and Biological SciencesStatistical hypothesis testingBiological Reviews
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Combining multiple hypothesis testing with machine learning increases the statistical power of genome-wide association studies

2016

Mieth, Bettina et al.

0301 basic medicineStatistical methodsComputer scienceGenome-wide association studyMachine learningcomputer.software_genreGenome-wide association studiesStatistical powerArticle[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Set (abstract data type)03 medical and health sciences[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG][MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]10007 Department of EconomicsStatistical significanceReplication (statistics)genomeStatistical hypothesis testingGenetic association1000 MultidisciplinaryMultidisciplinarybusiness.industryComputational scienceInstitut für Mathematik330 EconomicsSupport vector machine030104 developmental biologyMultiple comparisons problemwide association studiesstatistical methodsArtificial intelligencebusinesscomputer
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Partitioned learning of deep Boltzmann machines for SNP data.

2016

Abstract Motivation Learning the joint distributions of measurements, and in particular identification of an appropriate low-dimensional manifold, has been found to be a powerful ingredient of deep leaning approaches. Yet, such approaches have hardly been applied to single nucleotide polymorphism (SNP) data, probably due to the high number of features typically exceeding the number of studied individuals. Results After a brief overview of how deep Boltzmann machines (DBMs), a deep learning approach, can be adapted to SNP data in principle, we specifically present a way to alleviate the dimensionality problem by partitioned learning. We propose a sparse regression approach to coarsely screen…

0301 basic medicineStatistics and ProbabilityComputer scienceMachine learningcomputer.software_genre01 natural sciencesBiochemistryPolymorphism Single NucleotideMachine Learning010104 statistics & probability03 medical and health sciencessymbols.namesakeJoint probability distributionHumans0101 mathematicsMolecular BiologyStatistical hypothesis testingArtificial neural networkbusiness.industryGene Expression Regulation LeukemicDeep learningUnivariateComputational BiologyManifoldComputer Science ApplicationsData setComputational Mathematics030104 developmental biologyComputingMethodologies_PATTERNRECOGNITIONComputational Theory and MathematicsLeukemia MyeloidBoltzmann constantsymbolsData miningArtificial intelligencebusinesscomputerSoftwareCurse of dimensionalityBioinformatics (Oxford, England)
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Multiplicity- and dependency-adjusted p-values for control of the family-wise error rate

2016

Abstract Under the multiple testing framework, we propose the multiplicity- and dependency-adjustment method (MADAM) which transforms test statistics into adjusted p -values for control of the family-wise error rate. For demonstration, we apply the MADAM to data from a genetic association study.

0301 basic medicineStatistics and ProbabilityWord error rateMultiplicity (mathematics)Familywise error rateMadam01 natural sciences010104 statistics & probability03 medical and health sciences030104 developmental biologyStatisticsMultiple comparisons problemŠidák correctionPer-comparison error rate0101 mathematicsStatistics Probability and UncertaintyMathematicsStatistical hypothesis testingStatistics & Probability Letters
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Pitfalls of hypothesis tests and model selection on bootstrap samples: Causes and consequences in biometrical applications

2015

The bootstrap method has become a widely used tool applied in diverse areas where results based on asymptotic theory are scarce. It can be applied, for example, for assessing the variance of a statistic, a quantile of interest or for significance testing by resampling from the null hypothesis. Recently, some approaches have been proposed in the biometrical field where hypothesis testing or model selection is performed on a bootstrap sample as if it were the original sample. P-values computed from bootstrap samples have been used, for example, in the statistics and bioinformatics literature for ranking genes with respect to their differential expression, for estimating the variability of p-v…

0301 basic medicineStatistics and Probabilityeducation.field_of_studyComputer scienceModel selectionBootstrap aggregatingPopulationGeneral MedicineAsymptotic theory (statistics)01 natural sciences010104 statistics & probability03 medical and health sciences030104 developmental biologyResamplingStatisticsEconometrics0101 mathematicsStatistics Probability and UncertaintyeducationNull hypothesisQuantileStatistical hypothesis testingBiometrical Journal
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Statistical Explorations and Univariate Timeseries Analysis on COVID-19 Datasets to Understand the Trend of Disease Spreading and Death

2020

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0301 basic medicinetransmission ratepopulationSevere Acute Respiratory Syndromemedicine.disease_causelcsh:Chemical technologyBiochemistryRNNDisease OutbreaksAnalytical Chemistry0302 clinical medicinePandemiclcsh:TP1-1185030212 general & internal medicineInstrumentationVDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550Coronaviruskeraseducation.field_of_studypublic healthartificial intelligenceAtomic and Molecular Physics and OpticsRegressionmachine learningGeographySevere acute respiratory syndrome-related coronavirusstatisticsMiddle East Respiratory Syndrome Coronaviruscommunity diseaseregressionCoronavirus InfectionsLSTMPneumonia ViralPopulationWorld Health OrganizationArticleBetacoronavirusspread factor03 medical and health sciencesCode (cryptography)medicineAnimalsHumansElectrical and Electronic EngineeringeducationPandemicsmeasurable sensor dataalgorithmSARS-CoV-2ICDUnivariatedeep learningOutbreakCOVID-19medicine.diseasehypothesis testpython030104 developmental biologycorrelationCatsMiddle East respiratory syndromeCattleDemographySensors
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Rejoinder on: Natural Induction: An Objective Bayesian Approach

2009

Giron and Moreno. We certainly agree with Professors Giron and Moreno on the interest in sensitivity of any Bayesian result to changes in the prior. That said, we also consider of considerable pragmatic importance to be able to single out a unique, particular prior which may reasonably be proposed as the reference prior for the problem under study, in the sense that the corresponding posterior of the quantity of interest could be routinely used in practice when no useful prior information is available or acceptable. This is precisely what we have tried to do for the twin problems of the rule of succession and the law of natural induction. The discussants consider the limiting binomial versi…

Algebra and Number TheoryRule of successionApplied MathematicsBayesian probabilityComputational MathematicsPrior probabilityNatural (music)Geometry and TopologySensitivity (control systems)Problem of inductionNull hypothesisMathematical economicsAnalysisMathematicsStatistical hypothesis testing
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PATRONES DIFERENCIALES ENTRE PADRES Y PROFESORADO EN LA DETECCIÓN DE TDAH

2015

INTRODUCTION . The diagnosis of Attention Deficit Disorder with Hyperactivity (ADHD) has increased in recent years. The criteria for ADHD have become clearer in the scientific community. However, it is a complex disorder that requires the participation of a multidisciplinary team for an appropriate diagnosis. METHOD . Taking as a sample (N = 331) 6 to 9 year-old students from Cuenca, this study analyzed the existence of differential patterns between the two ratings, using the EMA-D.D.A. Scales (Garcia-Perez y Magaz, 2006). Different approaches to hypothesis testing are used, and the internal consistency of the scales is valued. RESULTS . The differences observed suggest differential influen…

Attention deficit disorderInternal consistencyeducationDevelopmental and Educational PsychologyBehavioral assessmentSchool screeningContext (language use)Observational studyMultidisciplinary teamPsychologyEducationDevelopmental psychologyStatistical hypothesis testingBordón. Revista de Pedagogía
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