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MPTinR: Analysis of Multinomial Processing Tree models with R

Singmann, Henrik and Kellen, David. (2013) MPTinR: Analysis of Multinomial Processing Tree models with R. Behavior Research Methods, 45 (2). pp. 560-575.

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Official URL: http://edoc.unibas.ch/51175/

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Abstract

We introduce MPTinR, a software package developed for the analysis of multinomial processing tree (MPT) models. MPT models represent a prominent class of cognitive measurement models for categorical data with applications in a wide variety of fields. MPTinR is the first software for the analysis of MPT models in the statistical programming language R, providing a modeling framework that is more flexible than standalone software packages. MPTinR also introduces important features such as (1) the ability to calculate the Fisher information approximation measure of model complexity for MPT models, (2) the ability to fit models for categorical data outside the MPT model class, such as signal detection models, (3) a function for model selection across a set of nested and nonnested candidate models (using several model selection indices), and (4) multicore fitting. MPTinR is available from the Comprehensive R Archive Network at http://cran.r-project.org/web/packages/MPTinR/ .
Faculties and Departments:07 Faculty of Psychology > Departement Psychologie > Forschungsbereich Sozial-, Wirtschafts- und Entscheidungspsychologie > Cognitive and Decision Sciences (Mata)
UniBasel Contributors:van der Kellen, David
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:Springer
e-ISSN:1554-3528
Note:Publication type according to Uni Basel Research Database: Journal article
Identification Number:
Last Modified:06 Feb 2018 15:28
Deposited On:06 Feb 2018 15:28

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