Eyelink eye trackers output a horrible mess, typically under
the form of a '.asc' file. The file in question is an assorted collection of
messages, events and raw data. This R package will attempt to make sense of it.
plyr, stringi, stringr, readr, magrittr, intervals
testthat, knitr, rmarkdown, dplyr, ggplot2, tidyr

Import ASC Files from EyeLink Eye Trackers
Imports plain-text ASC data files from EyeLink eye trackers
into (relatively) tidy data frames for analysis and visualization.
stringi, stringr, tibble, readr, intervals
testthat, knitr, rmarkdown, dplyr, ggplot2, tidyr, covr

Misc function for working with eyetracking data

c(
person("Jacob", "Dink", email = "jacobwdink@gmail.com", role = c("aut", "cre")),
person("Brock", "Ferguson", email = "brock.ferguson@gmail.com", role = c("aut"))
)
A set of tools that address 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.
pbapply, knitr, lme4 (>= 1.1-9), Matrix, testthat, rmarkdown
Jacob Dink [aut, cre],
Brock Ferguson [aut]

A set of tools that address 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.
pbapply, knitr, lme4 (>= 1.1-9), Matrix, testthat, rmarkdown,
doMC, foreach

pbapply, knitr, lme4 (>= 1.1-10), Matrix, testthat,
rmarkdown, doMC, foreach

c(
person("Samuel", "Forbes", email = "samuel.h.forbes@gmail.com", role = c("aut", "cre")),
person("Jacob", "Dink", email = "jacobwdink@gmail.com", role = c("aut")),
person("Brock", "Ferguson", email = "brock.ferguson@gmail.com", role = c("aut"))
)
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>.
pbapply, knitr, lme4 (>= 1.1-10), glmmTMB, MASS, Matrix,
testthat, rmarkdown, doMC, foreach
Samuel Forbes [aut, cre],
Jacob Dink [aut],
Brock Ferguson [aut]