PMID: identifier of
Pubmed reference: |
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 (16817511) |
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| title: |
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Modeling psychometric functions in R. |
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| author(s): |
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Rosa Yssaad-Fesselier1, Kenneth Knoblauch ( ) 1 |
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| laboratory: |
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| 1: |
Cerveau et vision |
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| INSERM : U371 РINRA РIFR19 РUniversit̩ Claude Bernard - Lyon I |
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| Centre de Recherche Inserm 18, Avenue du Doyen Lepine 69675 BRON CEDEX |
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| France |
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| abstract: |
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We demonstrate some procedures in the statistical computing environment R for obtaining maximum likelihood estimates of the parameters of a psychometric function by fitting a generalized nonlinear regression model to the data. A feature for fitting a linear model to the threshold (or other) parameters of several psychometric functions simultaneously provides a powerful tool for testing hypotheses about the data and, potentially, for reducing the number of parameters necessary to describe them. Finally, we illustrate procedures for treating one parameter as a random effect that would permit a simplified approach to modeling stimulus-independent variability due to factors such as lapses or interobserver differences. These tools will facilitate a more comprehensive and explicit approach to the modeling of psychometric data. |
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| subject: |
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Life Sciences/Human health and pathology/Sensory organs
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| fulltext language: |
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English |
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| ISSN: |
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1554-351X |
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| publication format: |
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Peer-reviewed article |
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| journal: |
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Behav Res Methods |
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| publication date: |
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2006-02 |
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| volume: |
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38 |
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| issue: |
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1 |
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| page, identifiant, ...: |
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28-41 |
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| MeSH Descriptor(s): |
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Computer Simulation – Humans – Likelihood Functions – Nonlinear Dynamics – Psychometrics |
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