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)