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irtrees

R package irtrees: Estimation of Tree-Based Item Response Models. Helper functions and example data sets accompanying De Boeck, P. and Partchev, I. (2012) IRTrees: Tree-Based Item Response Models of the GLMM Family, Journal of Statistical Software - Code Snippets, 48(1), 1-28.

Keywords for this software

Anything in here will be replaced on browsers that support the canvas element

  • item response theory
  • R
  • multinomial processing tree
  • eye-tracking data
  • sequential model
  • posterior model probability
  • latent trait models
  • trend
  • parameter heterogeneity
  • ordered responses
  • Bayesian model comparison
  • response time modeling
  • partial credit model
  • item response models
  • jstatsoft.org
  • lay beliefs about disease
  • generalized linear mixed effect model
  • mixture modeling
  • Bayesian model averaging
  • weakly ordered set
  • poset partitioned conditional IRT
  • intensive polytomous time series
  • Warp-III
  • Rasch model
  • hierarchical Bayesian modeling
  • multidimensional
  • poset
  • bridge sampling
  • multinomial processing tree model
  • diabetes

  • URL: cran.r-project.org/web...
  • Code
  • InternetArchive
  • Manual: cran.r-project.org/web...
  • Authors: Ivailo Partchev; Paul De Boeck
  • Dependencies: R

  • Add information on this software.


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References in zbMATH (referenced in 7 articles , 1 standard article )

Showing results 1 to 7 of 7.
y Sorted by year (citations)

  1. Cho, Sun-Joo; Brown-Schmidt, Sarah; De Boeck, Paul; Shen, Jianhong: Modeling intensive polytomous time-series eye-tracking data: a dynamic tree-based item response model (2020)
  2. Tutz, Gerhard: On the structure of ordered latent trait models (2020)
  3. Gronau, Quentin F.; Wagenmakers, Eric-Jan; Heck, Daniel W.; Matzke, Dora: A simple method for comparing complex models: Bayesian model comparison for hierarchical multinomial processing tree models using Warp-III bridge sampling (2019)
  4. Molenaar, Dylan; de Boeck, Paul: Response mixture modeling: accounting for heterogeneity in item characteristics across response times (2018)
  5. Ip, Edward H.; Chen, Shyh-Huei; Quandt, Sara A.: Analysis of multiple partially ordered responses to belief items with don’t know option (2016)
  6. Matzke, Dora; Dolan, Conor V.; Batchelder, William H.; Wagenmakers, Eric-Jan: Bayesian estimation of multinomial processing tree models with heterogeneity in participants and items (2015)
  7. Paul De Boeck, Ivailo Partchev: IRTrees: Tree-Based Item Response Models of the GLMM Family (2012) not zbMATH

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