Eye-Tracking Data Analysis R package eyetrackingR version 0.2.2 CRAN Task View: Tracking (https://CRAN.R-project.org/view=Tracking) 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>. Software 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 Samuel Forbes <samuel.h.forbes@gmail.com> Comprehensive R Archive Network (CRAN) Samuel Forbes [aut, cre], Jacob Dink [aut], Brock Ferguson [aut] MIT + file LICENSE (https://CRAN.R-project.org/package=eyetrackingR/LICENSE) 2025-06-18 application/tgz https://CRAN.R-project.org/package=eyetrackingR doi:10.32614/CRAN.package.eyetrackingR