Predicting Working Memory Failure: A Subjective Bayesian Approach to Model Selection

We use Bayes factors to compare two alternative characterizations of human working memory load in their ability to predict errors in database query-writing tasks. The first measures working memory load by the number of different features each task contains, while the second attempts instead to measu...

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Veröffentlicht in:	Journal of the American Statistical Association 1992-06, Vol.87 (418), p.319-327
Hauptverfasser:	Carlin, Bradley P., Kass, Robert E., Lerch, F. Javier, Huguenard, Brian R.
Format:	Artikel
Sprache:	eng
Schlagworte:	Applications and Case Studies Approximation Bayes factor Biological and medical sciences Case deletion Datasets Error rates Fundamental and applied biological sciences. Psychology Invoices Laplace method Memory Model choice Modeling Parametric models Prior elicitation Prior sensitivity Psychology. Psychoanalysis. Psychiatry Psychology. Psychophysiology Psychometrics. Statistics. Methodology Sensitivity analysis SQL Standard deviation Statistics. Mathematics Working memory
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