Addresses tasks along the pipeline from raw data to analysis and visualization for eye-tracking data. Offers several popular types of analyses, including linear and growth curve time analyses, onset-contingent reaction time analyses, as well as several non-parametric bootstrapping approaches. For references to the approach see Mirman, Dixon & Magnuson (2008) <doi:10.1016/j.jml.2007.11.006>, and Barr (2008) <doi:10.1016/j.jml.2007.09.002>.
| Version: | 0.2.2 |
| Depends: | R (≥ 3.2.0),dplyr (≥ 0.7.4) |
| Imports: | broom (≥ 0.3.7),broom.mixed,ggplot2 (≥ 2.0),lazyeval (≥0.1.10),rlang,zoo (≥ 1.7-12),tidyr (≥ 0.3.1),purrr (≥0.2.4) |
| Suggests: | pbapply,knitr,lme4 (≥ 1.1-10),glmmTMB,MASS,Matrix,testthat,rmarkdown,doMC,foreach |
| Published: | 2025-06-18 |
| DOI: | 10.32614/CRAN.package.eyetrackingR |
| Author: | Samuel Forbes [aut, cre], Jacob Dink [aut], Brock Ferguson [aut] |
| Maintainer: | Samuel Forbes <samuel.h.forbes at gmail.com> |
| BugReports: | https://github.com/samhforbes/eyetrackingR/issues |
| License: | MIT + fileLICENSE |
| URL: | https://samforbes.me/eyetrackingR/ |
| NeedsCompilation: | no |
| Citation: | eyetrackingR citation info |
| Materials: | README,NEWS |
| In views: | Tracking |
| CRAN checks: | eyetrackingR results |