psycho - Efficient and Publishing-Oriented Workflow for Psychological Science
The main goal of the psycho package is to provide tools for psychologists, neuropsychologists and neuroscientists, to facilitate and speed up the time spent on data analysis. It aims at supporting best practices and tools to format the output of statistical methods to directly paste them into a manuscript, ensuring statistical reporting standardization and conformity.
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apaapa6bayesiancorrelationformatinterpretationmixed-modelsneurosciencepsychopsychologyrstanarmstatistics
11.12 score 160 stars 3 dependents 924 scripts 812 downloads
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>.
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analogbayesianbetabrmschoicecognitivecomputationalconfidenceddmdecisionlognormalmodelsneuropsychologypsychologyresponsertsamplingscalessequentialstan
6.75 score 24 stars 39 scripts 249 downloads