R packages

BayesDiffIRT: Bayesian Diffusion Item Response Theory Models for Responses and Response Times

Diffusion Item Response Theory Models are latent variable models that explicitly take the dynamics of the decision process into account (Kang et al., 2022; van der Maas et al., 2011; Tuerlinckx & Boeck, 2005). The BayesDiffIRT package provides functions functions to sample posterior distributions and posterior predictive distributions of item and subject parameters of diffusion item response theory models for responses and reaction times. BayesDiffIRT also provides functions to visualize posterior distributions of diffusion item response theory model parameters and construct credible intervals. Under the hood, the package relies on NUTS sampling with STAN.
Authors: Manuel Rausch, Rainer W. Alexandrowicz
Maintainer: Manuel Rausch
Development version: https://github.com/ManuelRausch/bayesDiffIRT
Bug Reports: https://github.com/ManuelRausch/BayesDiffIRT/issues

statConfR: Models of Decision Confidence and Metacognition

The statConfR R package provides fitting functions and other tools for decision confidence and metacognition researchers, including meta-d′/d′ (Maniscalco and Lau, 2012), often considered to be the gold standard to measure metacognitive efficiency, and meta-information theoretic measures of metacognition. Also allows to fit and compare ten different static models of decision making and confidence to test the model underlying meta-d′/d′ and many applications of signal detection theory (see Rausch et al., 2023).
Authors: Manuel Rausch, Sascha Meyen, Sebastian Hellmann
Maintainer: Manuel Rausch
Development version: https://github.com/ManuelRausch/StatConfR
Release version: https://cran.r-project.org/web/packages/statConfR/index.html
Bug Reports: https://github.com/ManuelRausch/StatConfR/issues
Journal paper: Rausch, M., Meyen, S. & Hellmann, S. (2025). StatConfR: An R Package for Static Models of Decision Confidence and Metacognition. Journal of Open Source Software, 10(106), 6966. doi:10.21105/joss.06966 | full text

dynConfiR: Dynamic Models for Confidence and Response Time Distributions

The dynConfiR R package provides density functions for the joint distribution of choice, response time and confidence for discrete confidence judgments as well as functions for parameter fitting, prediction and simulation for various dynamical models of decision confidence (see Hellmann et al., 2023, and Hellmann et al., 2024, for detailed explanations of the different models), including the dynaViTE model, the dynWEV model, the 2DSD model (Pleskac & Busemeyer, 2010), and several race models.
Authors: Sebastian Hellmann, Manuel Rausch
Maintainer: Sebastian Hellmann
Development version: https://github.com/SeHellmann/dynConfiR
Release version: https://cran.r-project.org/web/packages/dynConfiR/index.html
Bug Reports: https://github.com/SeHellmann/dynConfiR/issues
Journal paper:Hellmann, S., Zehetleitner, M., & Rausch, M. (2026). dynConfiR: An R package for sequential sampling models of decision confidence. Behavior Research Methods. 58, 159. doi: 10.3758/s13428-026-03013-0 | full text from publisher