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Drift-Diffusion Model (DDM) has been widely used to model binary decision-making tasks, and many research studies the relationship between DDM parameters and other characteristics of the subject. This package uses 'RStan' to perform generalized liner regression analysis over DDM parameters via a single Bayesian Hierarchical model. Compared to estimating DDM parameters followed by a separate regression model, 'RegDDM' reduces bias and improves statistical power.
Version: | 1.0 |
Depends: | R (≥ 2.10) |
Imports: | rstan, stringr, dplyr, tidyr, purrr, rtdists, rlang, stats |
Suggests: | testthat (≥ 3.0.0) |
Published: | 2024-12-05 |
DOI: | 10.32614/CRAN.package.RegDDM |
Author: | Zekai Jin [aut, cre] |
Maintainer: | Zekai Jin <Jin.Zekai at nyspi.columbia.edu> |
BugReports: | https://github.com/biorabbit/RegDDM/issues |
License: | GPL (≥ 3) |
URL: | https://github.com/biorabbit/RegDDM |
NeedsCompilation: | no |
Materials: | README |
CRAN checks: | RegDDM results |
Reference manual: | RegDDM.pdf |
Package source: | RegDDM_1.0.tar.gz |
Windows binaries: | r-devel: RegDDM_1.0.zip, r-release: RegDDM_1.0.zip, r-oldrel: RegDDM_1.0.zip |
macOS binaries: | r-release (arm64): RegDDM_1.0.tgz, r-oldrel (arm64): RegDDM_1.0.tgz, r-release (x86_64): RegDDM_1.0.tgz, r-oldrel (x86_64): RegDDM_1.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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