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

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References in zbMATH (referenced in 8 articles , 1 standard article )

Showing results 1 to 8 of 8.
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. Tutz, Gerhard; Schneider, Micha: Flexible uncertainty in mixture models for ordinal responses (2019)
  5. Molenaar, Dylan; de Boeck, Paul: Response mixture modeling: accounting for heterogeneity in item characteristics across response times (2018)
  6. Ip, Edward H.; Chen, Shyh-Huei; Quandt, Sara A.: Analysis of multiple partially ordered responses to belief items with don’t know option (2016)
  7. 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)
  8. Paul De Boeck, Ivailo Partchev: IRTrees: Tree-Based Item Response Models of the GLMM Family (2012) not zbMATH