cogmod: Cognitive Models for Subjective Scales and Decision Making Tasks

Implements cognitive models for data from subjective (Likert or analog) scales and from decision making tasks with reaction times and choice data. Provides random generation, density functions, and custom response distributions for Bayesian estimation with 'brms', covering discreted-beta, ordered beta and choice-confidence models for subjective ratings, reaction-times families (Shifted Log-Normal, Shifted Wald), as well as sequential sampling models including the drift diffusion model (DDM), the racing diffusion model (RDM), the lognormal race model (LNR), and linear ballistic accumulator (LBA) model. The website provides examples and tutorials for using and interpreting the models. Methods are described in Ratcliff and McKoon (2008) <doi:10.1162/neco.2008.12-06-420>, Brown and Heathcote (2008) <doi:10.1016/j.cogpsych.2007.12.002>, Rouder et al. (2015) <doi:10.1007/s11336-013-9396-3>, Tillman et al. (2020) <doi:10.3758/s13423-020-01719-6>, Kubinec (2023) <doi:10.1017/pan.2022.20>, and Sciandra et al. (2024) <doi:10.1007/s10651-023-00592-5>.

Version:	0.3.0
Depends:	R (≥ 3.5.0)
Imports:	brms, insight, stats
Suggests:	testthat, cmdstanr, knitr, rmarkdown, loo, dplyr, ggplot2, ggrepel, easystats, datawizard, bayestestR, parameters, performance, modelbased, report, reformulas, lme4, RWiener, rtdists
Published:	2026-09-12
DOI:	10.32614/CRAN.package.cogmod (may not be active yet)
Author:	Dominique Makowski [aut, cre]
Maintainer:	Dominique Makowski <D.Makowski at sussex.ac.uk>
BugReports:	https://github.com/DominiqueMakowski/cogmod/issues
License:	MIT + file LICENSE
URL:	https://github.com/DominiqueMakowski/cogmod, https://dominiquemakowski.github.io/cogmod/
NeedsCompilation:	no
Additional_repositories:	https://mc-stan.org/r-packages/
Citation:	cogmod citation info
Materials:	NEWS
CRAN checks:	cogmod results

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