Package: cogmod 0.3.3

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 discrete beta, ordered beta and choice-confidence models for subjective ratings; reaction time distributions such as the ex-Gaussian and the shifted log-normal, Wald, gamma and Weibull; and sequential sampling models of choice and reaction time, including the drift diffusion model (DDM), the racing diffusion model (RDM), the lognormal race model (LNR) and the linear ballistic accumulator (LBA). 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>.

Authors:Dominique Makowski [aut, cre]