MPTinR: Analysis of multinomial processing tree models in R

Henrik Singmann, David Kellen

Research output: Contribution to journalArticle

64 Scopus citations

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/.

Original languageEnglish (US)
Pages (from-to)560-575
Number of pages16
JournalBehavior Research Methods
Volume45
Issue number2
DOIs
StatePublished - Jun 1 2013
Externally publishedYes

Keywords

  • Fisher information
  • MPT models
  • R
  • Software

ASJC Scopus subject areas

  • Experimental and Cognitive Psychology
  • Developmental and Educational Psychology
  • Arts and Humanities (miscellaneous)
  • Psychology (miscellaneous)
  • Psychology(all)

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