TreeBUGS

R package TreeBUGS. User-friendly analysis of hierarchical multinomial processing tree (MPT) models that are often used in cognitive psychology. Implements the latent-trait MPT approach (Klauer, 2010) and the beta-MPT approach (Smith & Batchelder, 2010) to model heterogeneity of participants. MPT models are conventiently specified by an .eqn-file as used by other MPT software. Data is either provided as comma-separated file (.csv) or directly in R. Models are either fitted by calling JAGS (Plummer, 2003) or by an MPT-tailored Gibbs sampler in C++ (only for nonhierarchical and beta MPT models). Provides tests of heterogeneity and MPT-tailored summaries and plotting functions.


References in zbMATH (referenced in 12 articles )

Showing results 1 to 12 of 12.
Sorted by year (citations)

  1. Bott, Franziska M.; Heck, Daniel W.; Meiser, Thorsten: Parameter validation in hierarchical MPT models by functional dissociation with continuous covariates: an application to contingency inference (2020)
  2. Erdfelder, Edgar (ed.); Hu, Xiangen (ed.); Rouder, Jeffrey N. (ed.); Wagenmakers, Eric-Jan (ed.): Cognitive psychometrics: the scientific legacy of William H. Batchelder (1940--2018) (2020)
  3. Groß, Julia; Pachur, Thorsten: Parameter estimation approaches for multinomial processing tree models: a comparison for models of memory and judgment (2020)
  4. Heck, Daniel W.; Noventa, Stefano: Representing probabilistic models of knowledge space theory by multinomial processing tree models (2020)
  5. Jobst, Lisa J.; Heck, Daniel W.; Moshagen, Morten: A comparison of correlation and regression approaches for multinomial processing tree models (2020)
  6. Kellen, David; Klauer, Karl Christoph: Selecting amongst multinomial models: an apologia for normalized maximum likelihood (2020)
  7. Michalkiewicz, Martha; Horn, Sebastian S.; Bayen, Ute J.: Hierarchical multinomial modeling to explain individual differences in children’s clustering in free recall (2020)
  8. Schnuerch, Martin; Erdfelder, Edgar; Heck, Daniel W.: Sequential hypothesis tests for multinomial processing tree models (2020)
  9. 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)
  10. Heck, Daniel W.: Accounting for estimation uncertainty and shrinkage in Bayesian within-subject intervals: a comment on Nathoo, Kilshaw, and Masson (2018) (2019)
  11. Heck, Daniel W.; Erdfelder, Edgar; Kieslich, Pascal J.: Generalized processing tree models: jointly modeling discrete and continuous variables (2018)
  12. Schweickert, Richard; Zheng, Xiaofang: Tree inference: selective influence in multinomial processing trees with supplementary measures such as response time (2018)