Search results for " Inference"

showing 10 items of 337 documents

Automatic regrouping of strata in the goodness-of-fit chi-square test

2019

Pearson’s chi-square test is widely employed in social and health sciences to analyze categorical data and contingency tables. For the test to be valid, the sample size must be large enough to provide a minimum number of expected elements per category. This paper develops functions for regrouping strata automatically no matter where they are located, thus enabling the goodness-of-fit test to be performed within an iterative procedure. The functions are written in Excel VBA (Visual Basic for Applications) and in Mathematica. The usefulness and performance of these functions is illustrated by means of a simulation study and the application to different datasets. Finally, the iterative use of …

Contingency tableComputer scienceContinuous Sample of Working Lives62G10 62P25MathematicaSample (statistics):62 Statistics::62P Applications [Classificació AMS]Visual Basic for ApplicationsEconomiaTest (assessment):62 Statistics::62G Nonparametric inference [Classificació AMS]Goodness of fitFinancesSample size determination:Matemàtiques i estadística::Estadística matemàtica [Àrees temàtiques de la UPC]StatisticsVisual Basic for ApplicationsChi-square testGoodness-of-fit chi-square test statistical software Visual Basic for Applications Mathematica Continuous Sample of Working Livesstatistical softwareGoodness-of-fit chi-square testEconometríaCategorical variable
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Inference for the interclass correlation in familial data using small sample asymptotics

2012

Inference on the parent-offspring correlation coefficient is an important problem in the analysis of familial data, and point estimates and likelihood based inference are available in the literature. In this work, corrections for the signed log-likelihood ratio test statistics are proposed, based on small sample asymptotics, in order to achieve accurate small sample performance. The corrected statistic can be used for hypothesis testing as well as for interval estimation.

Correlation coefficientInterclass correlationInterval estimationStatisticsFiducial inferenceInferencePoint estimationStatisticMathematicsStatistical hypothesis testingAIP Conference Proceedings
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Finite Sample Sizes of the GRS Test in the Presence of Dynamic Correlation and Conditional Heteroskedasticity

2017

This paper investigates the finite sample properties of the widely-used Gibbons, Ross, Shanken (1989) (GRS) test in the presence of both conditional correlation and conditional heteroskedasticity. It finds that the GRS test exhibits serious size distortions resulting in potentially misleading statistical inferences. The correct critical values, as reported in the study, are considerably larger than suggested by the GRS test.

CorrelationHeteroscedasticitySample size determinationStatisticsStatistical inferenceEconometricsSample (statistics)Wald testMathematicsTest (assessment)SSRN Electronic Journal
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Convergence of Agents' and Targets' Reports on Intraorganizational Influence Attempts1

2003

Summary The object of the current study was to determine the convergent and discriminant validity of agents' and targets' reports on intraorganizational influence attempts with a structural equation model using latent state-trait analyses. To explain agent-target convergence, we linked the theory of formal organizations to Correspondent Inference Theory. Managers (agents) were asked to describe how they try to influence their boss, a coworker, and a subordinate. These targets also described how the agent tries to influence them. Both agents and targets rated four types of influence attempts twice within 2½ months, namely, rational persuasion, ingratiation, pressure, and upward appeals. In …

Correspondent inference theoryPersuasionBossIngratiationmedia_common.quotation_subjectDiscriminant validityConvergence (relationship)PsychologyObject (philosophy)Social psychologyApplied PsychologyStructural equation modelingmedia_commonEuropean Journal of Psychological Assessment
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Causal Inference and Statistical Fallacies

2001

Fallacies are defined as plausible-seeming arguments that give the wrong conclusion. The article concentrates on those with some connection with causality. The classical definition of causality involving a necessary and sufficient condition for an effect is rejected and three possible definitions discussed. The first is that of a statistical association that cannot be explained away as the effect of admissible alternative features. To make this more precise, Markov graphical representations are introduced and the important distinction between pairs of variables on an equal footing and those in a potential explanatory-response relation described. The roles of unobserved confounders and of ra…

Counterfactual thinkingMarkov chainArgumentCausal inferenceReading (process)media_common.quotation_subjectRelation (history of concept)Mathematical economicsCausalitySocial psychologyMisuse of statisticsMathematicsmedia_common
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The role of blood DNA methylation in environment-related chronic disease: a biostatistical toolkit

2013

La epigenética se refiere al estudio de las marcas químicas que alteran la expresión génica sin cambiar la secuencia genética. Los factores ambientales y conductuales son conocidos modificadores de la epigenética, resultando así en cambios heredables que pueden dar lugar a alteraciones en procesos biológicos esenciales y, por consiguiente, al desarrollo de enfermedades. La metilación del ADN es la marca epigenética más estudiada. Existe amplia evidencia científica de la asociación entre factores ambientales tales como tabaco y metales, y desregulaciones en la metilación del ADN. Asimismo, existe amplia evidencia de la asociación entre desregulaciones en metilación del ADN y enfermedades cró…

DNA methylationomics dataUNESCO::CIENCIAS MÉDICAScausal inferencesurvival analysisUNESCO::MATEMÁTICAS
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Network reconstruction for trans acting genetic loci using multi-omics data and prior information.

2022

Background: Molecular measurements of the genome, the transcriptome, and the epigenome, often termed multi-omics data, provide an in-depth view on biological systems and their integration is crucial for gaining insights in complex regulatory processes. These data can be used to explain disease related genetic variants by linking them to intermediate molecular traits (quantitative trait loci, QTL). Molecular networks regulating cellular processes leave footprints in QTL results as so-called trans-QTL hotspots. Reconstructing these networks is a complex endeavor and use of biological prior information can improve network inference. However, previous efforts were limited in the types of priors…

Data Integrationeducation.field_of_studyComputer scienceScale (chemistry)Bayesian probabilityPopulationQuantitative Trait LociBiological databaseInferenceData Integration ; Machine Learning ; Multi-omics ; Network Inference ; Personalized Medicine ; Prior Information ; Simulation ; Systems BiologyComputational biologyQuantitative trait locusReplication (computing)Machine LearningPrior probabilityCohortGeneticsMolecular MedicineHumans:Medicine [Science]Gene Regulatory NetworkseducationTranscriptomeMolecular BiologyGenetics (clinical)Genome medicine
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Data Augmentation Approach in Bayesian Modelling of Presence-only Data

2011

Abstract Ecologists are interested in prediction of potential distribution of species in suitable areas, essential for planning conservation and management strategies. Unfortunately, often the only available information in such studies is the true presence of the species at few locations of the study area and the associated environmental covariates over the entire area, referred as presence-only data. We propose a Bayesian approach to estimate logistic linear regressions adapted to presence-only data through the introduction of a random approximation of the correction factor in the adjusted logistic model that allows us to overcome the need to know a priori the prevalence of the species.

Data augmentationPresence-only dataComputer scienceBayesian probabilityLogistic regressionBayesian inferencePseudo-absence approachBayesian statisticsBayesian model; Data augmentation; MCMC algorithm; Potential distribution; Presence-only data; Pseudo-absence approachBayesian model Data augmentation MCMC algorithm Presence-only data Pseudo-absence approach Potential distributionpotentialdistributionBayesian modelBayesian multivariate linear regressionPotential distributionStatisticsCovariateEconometricsGeneral Earth and Planetary Sciencespseudo-absence approach; potentialdistribution.; data augmentation; presence-only data; potential distribution; mcmc algorithm; bayesian modelBayesian linear regressionBayesian averageMCMC algorithmGeneral Environmental ScienceProcedia Environmental Sciences
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A Fuzzy Inference Expert System to Support the Decision of Deploying a Military Naval Unit to a Mission

2009

Naval military units are complex systems required to operate in fixed time frames in offshore tasks where maintenance operations are drastically limited. A failure during a mission is a critical event that can drastically influence the mission success. The decision of switching a unit to a mission hence requires complex judgments involving information about the health status of machineries and the environmental conditions. The present procedure aims to support the decision about switching a unit to a mission considering the vagueness and uncertainty of information by means of fuzzy theory and emulates the decision process of a human expert by means of a rule-based inference engine. A numeri…

Decision support systemOperations researchComputer scienceIntelligent decision support systemComplex systemComputerApplications_COMPUTERSINOTHERSYSTEMSVaguenesscomputer.software_genreFuzzy logicExpert systemUnit (housing)fuzzy inference decision support system mission reliabilityiSettore ING-IND/17 - Impianti Industriali MeccaniciInference enginecomputer
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The Effective Sample Size

2013

Model selection procedures often depend explicitly on the sample size n of the experiment. One example is the Bayesian information criterion (BIC) criterion and another is the use of Zellner–Siow priors in Bayesian model selection. Sample size is well-defined if one has i.i.d real observations, but is not well-defined for vector observations or in non-i.i.d. settings; extensions of critera such as BIC to such settings thus requires a definition of effective sample size that applies also in such cases. A definition of effective sample size that applies to fairly general linear models is proposed and illustrated in a variety of situations. The definition is also used to propose a suitable ‘sc…

Deviance information criterionEconomics and EconometricsBayesian information criterionSample size determinationModel selectionPrior probabilityStatisticsLinear modelBayesian inferenceAlgorithmSelection (genetic algorithm)Statistics::ComputationMathematicsEconometric Reviews
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