Search results for "regression"

showing 10 items of 2619 documents

Women’s empowerment and child mortality: the case of Bangladesh

2018

Bangladesh is the Southern Asian country that has been experiencing the highest absolute decline in the Under Five Mortality Rate in the past 15 years. This paper focuses on the importance of women’s education and empowerment variables in explaining this extraordinary result. We use a twolevel multilevel logistic regression to take into account the great differences among territorial communities in terms of child mortality reduction. It emerges that the importance of woman’s empowerment - measured as individual and as mother - remains relevant even when the context is considered. A sensitivity analysis has been conducted to test the relevance of different indicators of female empowerment.
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The association between body mass, metabolic rates and survival of bank voles

2009

Summary 1Many studies have been performed in an attempt to explain physiological, ecological and evolutionary factors behind inter- and intraspecific variation in basal metabolic rate (BMR) and maximum aerobic metabolic rate (VO2max). However, very little is known about the association between the traits and fitness components in populations of free-living animals. 2We studied the association between body size and the metabolic rates of bank voles Myodes (= Clethrionomys) glareolus and their survival, measured by repeated trappings across 2 years in an isolated, island population. All measured traits (body mass, BM; head width, HW; VO2max and BMR) were significantly repeatable over short (m…

Basal rateEvolutionary physiologyeducation.field_of_studyevolutionary physiologyEcologyPopulationBiologyLogistic regressionoxygen consumptionsurvivalIntraspecific competitionAnimal sciencefitnessBasal metabolic rateGenetic variationmammalsStabilizing selectioneducationEcology Evolution Behavior and SystematicsFunctional Ecology
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Making Every "Point" Count: Identifying the Key Determinants of Team Success in Elite Men’s Wheelchair Basketball

2019

Wheelchair basketball coaches and researchers have typically relied on box score data and the Comprehensive Basketball Grading System to inform practice, however, these data do not acknowledge how the dynamic perspectives of teams change, vary and adapt during possessions in relation to the outcome of a game. Therefore, this study aimed to identify the key dynamic variables associated with team success in elite men’s wheelchair basketball and explore the impact of each key dynamic variable upon the outcome of performance through the use of binary logistic regression modelling. The valid and reliable template developed by Francis, Owen and Peters (2019) was used to analyse video footage in S…

Basketballlcsh:BF1-990Applied psychologyLogistic regression050105 experimental psychologyOddsData modelingRC120003 medical and health sciences0302 clinical medicineParalympicPsychology0501 psychology and cognitive sciencesCategorical variableGeneral PsychologyOriginal Researchlogistic regression05 social sciencesOffensiveVDP::Medisinske Fag: 700::Idrettsmedisinske fag: 850sport performance analysisEuropean championshipslcsh:PsychologyElitePsychologypredictive modeling030217 neurology & neurosurgeryPredictive modelling
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Bayesian Methodology in Statistics

2009

Bayesian methods provide a complete paradigm for statistical inference under uncertainty. These may be derived from an axiomatic system and provide a coherent methodology which makes it possible to incorporate relevant initial information, and which solves many of the difficulties that frequentist methods are known to face. If no prior information is to be assumed, the more frequent situation met in scientific reporting, a formal initial prior function, the reference prior, mathematically derived from the assumed model, is used; this leads to objective Bayesian methods, objective in the precise sense that their results, like frequentist results, only depend on the assumed model and the data…

Bayesian statisticsBayes' theoremFrequentist inferenceStatisticsPrior probabilityBayesian hierarchical modelingBayes factorBayesian inferenceBayesian linear regressionMathematics
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Protective role of mindfulness, self-compassion and psychological flexibility on the burnout subtypes among psychology and nursing undergraduate stud…

2021

Abstract To explore the relationship between mindfulness, self-compassion and psychological flexibility, and the burnout subtypes in university students of the Psychology and Nursing degrees, and to analyse possible risk factors for developing burnout among socio-demographic and studies-related characteristics. Design Cross-sectional study conducted on a sample of 644 undergraduate students of Nursing and Psychology from two Spanish universities. Methods The study was conducted between December 2015 and May 2016. Bivariate Pearson's correlations were computed to analyse the association between mindfulness facets, self-compassion and psychological flexibility, and levels of burnout. Multivar…

Bienestar del estudianteMindfulnesshealth care facilities manpower and servicesEnfermedad profesionalCalidad de la vida laboraleducationBivariate analysisBurnoutLogistic regression03 medical and health sciences0302 clinical medicineNursinghealth services administrationBayesian multivariate linear regressionHumansMeditación030212 general & internal medicineAssociation (psychology)Burnout ProfessionalGeneral Nursing030504 nursingFlexibility (personality)Cross-Sectional StudiesAtención plenaStudents NursingEmpathy0305 other medical sciencePsychologyMindfulnesspsychological phenomena and processesSelf-compassionJournal of advanced nursingREFERENCES
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Deep learning and process understanding for data-driven Earth system science

2017

Machine learning approaches are increasingly used to extract patterns and insights from the ever-increasing stream of geospatial data, but current approaches may not be optimal when system behaviour is dominated by spatial or temporal context. Here, rather than amending classical machine learning, we argue that these contextual cues should be used as part of deep learning (an approach that is able to extract spatio-temporal features automatically) to gain further process understanding of Earth system science problems, improving the predictive ability of seasonal forecasting and modelling of long-range spatial connections across multiple timescales, for example. The next step will be a hybri…

Big DataTime FactorsProcess modelingGeospatial analysis010504 meteorology & atmospheric sciencesProcess (engineering)0208 environmental biotechnologyBig dataGeographic Mapping02 engineering and technologycomputer.software_genreMachine learning01 natural sciencesPattern Recognition AutomatedData-drivenDeep LearningSpatio-Temporal AnalysisHumansComputer SimulationWeather0105 earth and related environmental sciencesMultidisciplinarybusiness.industryDeep learningUncertaintyReproducibility of ResultsTranslatingRegression Psychology020801 environmental engineeringEarth system scienceKnowledgePattern recognition (psychology)Earth SciencesFemaleSeasonsArtificial intelligencebusinessPsychologyFacial RecognitioncomputerForecastingNature
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Estimation of total electricity consumption curves of small areas by sampling in a finite population

2016

International audience; Many studies carried out in the French electricity company EDF are based on the analysis of the total electricity consumption curves of groups of customers. These aggregated electricity consumption curves are estimated by using samples of thousands of curves measured at a small time step and collected according to a sampling design. Small area estimation is very usual in survey sampling. It is often addressed by using implicit or explicit domain models between the interest variable and the auxiliary variables. The goal here is to estimate totals of electricity consumption curves over domains or areas. Three approaches are compared: the rst one consists in modeling th…

Big dataEnergyMSC: 62H25Functional principal component analysis[MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]Regression trees[ MATH.MATH-ST ] Mathematics [math]/Statistics [math.ST]Mixed modelsFunctional data[MATH.MATH-ST] Mathematics [math]/Statistics [math.ST]
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2013

Currently, a growing number of programs become available in statistical software for multiple imputation of missing values. Among others, two algorithms are mainly implemented: Expectation Maximization (EM) and Multiple Imputation by Chained Equations (MICE). They have been shown to work well in large samples or when only small proportions of missing data are to be imputed. However, some researchers have begun to impute large proportions of missing data or to apply the method to small samples. A simulation was performed using MICE on datasets with 50, 100 or 200 cases and four or eleven variables. A varying proportion of data (3% - 63%) was set as missing completely at random and subsequent…

Binary responseSample size determinationStatisticsExpectation–maximization algorithmEconometricsMain effectImputation (statistics)Missing dataInteractionLogistic regressionMathematicsOpen Journal of Statistics
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Prediction models based on soil properties for evaluating the uptake of eight heavy metals by tomato plant (Lycopersicon esculentum Mill.) grown in a…

2021

The aim of this study is to design de novo prediction models in order to gauge the likely uptake of eight heavy metals (Al, Cr, Cu, Fe, Mn, Ni, Pb and Zn) by Lycopersicon esculentum, the tomato plant. Uptake was assessed within the plant’s root, stem, leaf and fruit tissues, respectively. The plant was cultivated in soil amended by different application rates of sewage sludge, i.e. 0, 10, 20, 30 and 40 g/kg. The roots exhibited markedly elevated heavy metal concentrations compared to the above-ground plant components, with the exception of the quantity of Ni in the leaves. Apart from Al, Fe and Mn, a bioconcentration factor >1 was identified for all heavy metals. Excluding Ni in the leaves,…

Bioconcentration and translocation factorsBiosolidsSoil amendmentBioconcentrationTomatoLycopersiconMetalChemical Engineering (miscellaneous)Waste Management and DisposalbiologyChemistrybusiness.industryProcess Chemistry and TechnologyHeavy metalsRegression modelsbiology.organism_classificationPollutionHorticultureBiosolidsMetalsAgriculturevisual_artSoil watervisual_art.visual_art_mediumbusinessSludgeJournal of Environmental Chemical Engineering
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Measurement of lean body mass using bioelectrical impedance analysis: a consideration of the pros and cons

2017

The assessment of body composition has important applications in the evaluation of nutritional status and estimating potential health risks. Bioelectrical impedance analysis (BIA) is a valid method for the assessment of body composition. BIA is an alternative to more invasive and expensive methods like dual-energy X-ray absorptiometry, computerized tomography, and magnetic resonance imaging. Bioelectrical impedance analysis is an easy-to-use and low-cost method for the estimation of fat-free mass (FFM) in physiological and pathological conditions. The reliability of BIA measurements is influenced by various factors related to the instrument itself, including electrodes, operator, subject, a…

Bioelectrical impedance analysismedicine.medical_specialtyAgingNutritional Status030209 endocrinology & metabolismBody composition03 medical and health sciences0302 clinical medicineElderlyThinnessBioelectrical impedance analysis Body composition Elderly Prediction equationsStatisticsmedicineElectric ImpedanceHumans030212 general & internal medicineMuscle SkeletalMathematicsBioelectrical impedance analysis; Body composition; Elderly; Prediction equationsGeriatrics gerontologyReproducibility of ResultsRegression analysisNutritional statusPrediction equationsSkeletal muscle massSurgeryLean body massRegression AnalysisGeriatrics and GerontologyBioelectrical impedance analysis
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