AppleTree: a multinomial processing tree modeling program for Macintosh computers

Multinomial processing tree (MPT) models are statistical models that allow for the prediction of categorical frequency data by sets of unobservable (cognitive) states. In MPT models, the probability that an event belongs to a certain category is a sum of products of state probabilities. AppleTree is...

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Bibliographic Details
Published in:Behavior research methods, instruments, & computers instruments, & computers, 1999-11, Vol.31 (4), p.696-700
Main Author: Rothkegel, R
Format: Article
Language:English
Subjects:
Cognition
Data Interpretation, Statistical
Humans
Models, Statistical
Psychology, Experimental - methods
Software
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Summary:Multinomial processing tree (MPT) models are statistical models that allow for the prediction of categorical frequency data by sets of unobservable (cognitive) states. In MPT models, the probability that an event belongs to a certain category is a sum of products of state probabilities. AppleTree is a computer program for Macintosh for testing user-defined MPT models. It can fit model parameters to empirical frequency data, provide confidence intervals for the parameters, generate tree graphs for the models, and perform identifiability checks. In this article, the algorithms used by AppleTree and the handling of the program are described.
ISSN:0743-3808
1532-5970
DOI:10.3758/BF03200748