R version 4.3.0 (2023-04-21)
Platform: aarch64-apple-darwin20 (64-bit)
Running under: macOS Ventura 13.2.1
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRlapack.dylib; LAPACK version 3.11.0
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
time zone: Europe/Berlin
tzcode source: internal
attached base packages:
[1] stats graphics grDevices datasets utils methods base
loaded via a namespace (and not attached):
[1] htmlwidgets_1.6.2 compiler_4.3.0 fastmap_1.1.1 cli_3.6.1
[5] htmltools_0.5.5 tools_4.3.0 rstudioapi_0.15.0 yaml_2.3.7
[9] rmarkdown_2.23 knitr_1.43 jsonlite_1.8.7 xfun_0.39
[13] digest_0.6.33 rlang_1.1.1 renv_0.17.3 evaluate_0.21 Reproducible analysis reports with eye-tracking reading time data
Summer Semester 2023
Course Intro
Welcome to the website for the course “Reproducible analysis reports with eye-tracking reading time data” for the Summer Semester 2023. Some quick info about the course:
- the language of instruction is English
- Block course:
- April 12-14 (10am-4pm)
- June 30th (2-6pm)
- July 1st (10am-4pm)
Most documents are available as slides, html, and PDF on Moodle. Choose whichever you prefer (I suggest html).
Course description
- develop skills and know-how
- create reproducible reports & presentations of eye-tracking reading data
- common measures in eye-tracking reading
- importance of reproducible workflow
- communicate findings
- hands-on exercises in RStudio with the R programming language
- data wrangling (
tidyverse) - data visualisation (
ggplot2), - descriptive and inferential statistics (
lme4andlmerTest)
- data wrangling (
Course credits
- 4 LP
- attendance and participation: 1LP
- In-class exercises and preparation: 1LP
- Assignments: 2 LP
- Reproducible (pilot) analysis report + Pre-registration
- Reproducible analysis report
Reading list
- this course does not have a heavy reading load, but a few readings are strongly recommended:
- Open Science: (kathawalla_easing_2021?)
- Eye-tracking reading: (clifton_eye_2007?); (vasishth_what_2013?);
- A short recommendation for statistics for psycholinguists: (vasishth_statistical_2016?)
- Statistics for Linguistics (textbook): (winter_statistics_2019?) (E-book available via Grimm)
Further readings
- there are lots of useful resources out there, specifically:
- Bodo Winter’s tutorials on linear (mixed) models (winter_linear_2013?; winter_very_2014?)
- the PsyTeachR website is a great resource for hands-on stats and/or data analysis in R from the University of Glasgow School of Psychology and Neuroscience
Session Info
Save your session info at the end of each document. Our results very often depend on the version of R/RStudio/a package we used. This is a great first step towards creating a reproducible workflow!