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cogmod  

Cognitive Models for Subjective Scales and Decision Making Tasks
View on CRAN: Click here


Download and install cogmod package within the R console
Install from CRAN:
install.packages("cogmod")

Install from Github:
library("remotes")
install_github("cran/cogmod")

Install by package version:
library("remotes")
install_version("cogmod", "0.3.3")



Attach the package and use:
library("cogmod")
Maintained by
Dominique Makowski
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-09-12
Latest Update: 2026-09-12
Description:
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>.
How to cite:
Dominique Makowski (2026). cogmod: Cognitive Models for Subjective Scales and Decision Making Tasks. R package version 0.3.3, https://cran.r-project.org/web/packages/cogmod. Accessed 03 Oct. 2026.
Previous versions and publish date:
(2026-09-25 23:50), 0.3.0 (2026-09-12 10:10)
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Complete documentation for cogmod
Functions, R codes and Examples using the cogmod R package
Full cogmod package functions and examples
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