Painfree and accurate Bayesian estimation of psychometric functions for (potentially) overdispersed data.

Schütt, Heiko H; Harmeling, Stefan; Macke, Jakob H; Wichmann, Felix A

Schütt, Heiko H; Harmeling, Stefan; Macke, Jakob H; Wichmann, Felix A.

Afiliação

Schütt HH; Neural Information Processing Group, University of Tübingen, Tübingen, Germany; Department of Psychology, Universität of Potsdam, Potsdam, Germany; Graduate School for Neural and Behavioural Sciences IMPRS, Tübingen, Germany. Electronic address: heiko.schuett@uni-tuebingen.de.
Harmeling S; Institut für Informatik, Heinrich-Heine-Universität Düsseldorf, Germany.
Macke JH; Research Center Caesar, Bonn, Germany; Max Planck Institute for Biological Cybernetics, Tübingen, Germany; Bernstein Center for Computational Neuroscience, Tübingen, Germany.
Wichmann FA; Neural Information Processing Group, University of Tübingen, Tübingen, Germany; Bernstein Center for Computational Neuroscience, Tübingen, Germany; Max Planck Institute for Intelligent Systems, Tübingen, Germany. Electronic address: felix.wichmann@uni-tuebingen.de.

Vision Res ; 122: 105-123, 2016 05.

Article em En | MEDLINE | ID: mdl-27013261

Assuntos

Teorema de Bayes; Interpretação Estatística de Dados; Psicometria/métodos; Psicofísica/métodos; Humanos; Modelos Estatísticos; Limiar Sensorial

Palavras-chave

Bayesian inference; Beta-binomial model; Confidence intervals; Credible intervals; Non-stationarity; Overdispersion; Psychometric function; Psychophysical methods

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Psicometria / Psicofísica / Interpretação Estatística de Dados / Teorema de Bayes Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2016 Tipo de documento: Article

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