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 + file LICENSE URL: https://samforbes.me/eyetrackingR/ NeedsCompilation: no Citation: eyetrackingR citation info Materials: README NEWS In views: Tracking CRAN checks: eyetrackingR resultsRetroSearch is an open source project built by @garambo | Open a GitHub Issue
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