eyetrackingR: Eye-Tracking Data Analysis

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: 0.2.0
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: 2021-09-27
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: http://www.eyetracking-r.com/
NeedsCompilation: no
Citation: eyetrackingR citation info
Materials: README NEWS
CRAN checks: eyetrackingR results

Documentation:

Reference manual: eyetrackingR.pdf
Vignettes: Estimating time windows of divergence
Performing a growth curve analysis
Performing an onset-contingent analysis
Preparing your data for eyetrackingR
Performing a window analysis

Downloads:

Package source: eyetrackingR_0.2.0.tar.gz
Windows binaries: r-devel: eyetrackingR_0.2.0.zip, r-release: eyetrackingR_0.2.0.zip, r-oldrel: eyetrackingR_0.2.0.zip
macOS binaries: r-release (arm64): eyetrackingR_0.2.0.tgz, r-release (x86_64): eyetrackingR_0.2.0.tgz, r-oldrel: eyetrackingR_0.2.0.tgz
Old sources: eyetrackingR archive

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