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A test of the diffusion model explanation for the worst performance rule using preregistration and blinding.
Dutilh, Gilles; Vandekerckhove, Joachim; Ly, Alexander; Matzke, Dora; Pedroni, Andreas; Frey, Renato; Rieskamp, Jörg; Wagenmakers, Eric-Jan.
Afiliação
  • Dutilh G; Department of Psychology, University of Basel, Missionsstrasse 60/62, 4055, Basel, Switzerland. gilles.dutilh@gmail.com.
  • Vandekerckhove J; University of California Irvine, Irvine, CA, USA.
  • Ly A; University of Amsterdam, Amsterdam, The Netherlands.
  • Matzke D; University of Amsterdam, Amsterdam, The Netherlands.
  • Pedroni A; Department of Psychology, University of Basel, Missionsstrasse 60/62, 4055, Basel, Switzerland.
  • Frey R; Department of Psychology, University of Basel, Missionsstrasse 60/62, 4055, Basel, Switzerland.
  • Rieskamp J; Department of Psychology, University of Basel, Missionsstrasse 60/62, 4055, Basel, Switzerland.
  • Wagenmakers EJ; University of Amsterdam, Amsterdam, The Netherlands.
Atten Percept Psychophys ; 79(3): 713-725, 2017 Apr.
Article em En | MEDLINE | ID: mdl-28233280
ABSTRACT
People with higher IQ scores also tend to perform better on elementary cognitive-perceptual tasks, such as deciding quickly whether an arrow points to the left or the right Jensen (2006). The worst performance rule (WPR) finesses this relation by stating that the association between IQ and elementary-task performance is most pronounced when this performance is summarized by people's slowest responses. Previous research has shown that the WPR can be accounted for in the Ratcliff diffusion model by assuming that the same ability parameter-drift rate-mediates performance in both elementary tasks and higher-level cognitive tasks. Here we aim to test four qualitative predictions concerning the WPR and its diffusion model explanation in terms of drift rate. In the first stage, the diffusion model was fit to data from 916 participants completing a perceptual two-choice task; crucially, the fitting happened after randomly shuffling the key variable, i.e., each participant's score on a working memory capacity test. In the second stage, after all modeling decisions were made, the key variable was unshuffled and the adequacy of the predictions was evaluated by means of confirmatory Bayesian hypothesis tests. By temporarily withholding the mapping of the key predictor, we retain flexibility for proper modeling of the data (e.g., outlier exclusion) while preventing biases from unduly influencing the results. Our results provide evidence against the WPR and suggest that it may be less robust and less ubiquitous than is commonly believed.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Desempenho Psicomotor / Inteligência / Memória de Curto Prazo / Modelos Psicológicos Tipo de estudo: Prognostic_studies / Qualitative_research Limite: Adolescent / Adult / Female / Humans / Male Idioma: En Revista: Atten Percept Psychophys Assunto da revista: PSICOFISIOLOGIA / PSICOLOGIA Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Suíça

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Desempenho Psicomotor / Inteligência / Memória de Curto Prazo / Modelos Psicológicos Tipo de estudo: Prognostic_studies / Qualitative_research Limite: Adolescent / Adult / Female / Humans / Male Idioma: En Revista: Atten Percept Psychophys Assunto da revista: PSICOFISIOLOGIA / PSICOLOGIA Ano de publicação: 2017 Tipo de documento: Article País de afiliação: Suíça