PupilPre0.6.2 package

Preprocessing Pupil Size Data

apply_butter

Applies a Butterworth filter to each event.

apply_cleanup_change

Applies user-selected changes to auto cleanup

apply_user_cleanup

Applies manual cleanup to the data

baseline

Baseline correct the data

blink_summary

Check blinks

butter_filter_app

Plots the effect of Butterworth filtering by event.

check_baseline

Check baseline window for missing data

clean_artifact

Automatically clean artifacts.

clean_blink

Automatically clean Eyelink marked blinks.

compare_summary

A utility function to compare pupil size data before and after applyin...

downsample

Downsample the data

interpolate_NAs

Interpolation for missing data.

NA_summary

Check missing data

plot_compare_app

Plots comparison of Pupil and Pupil_Previous by event.

plot_events

Plot each event within a group to a directory

plot_summary_app

Plots summary of subject or item.

ppl_check_eye_recording

Check which eyes were recorded during the experiment

ppl_plot_avg

Plots average Pupil.

ppl_plot_avg_cdiff

Plots average difference between two conditions.

ppl_plot_avg_contour

Plots average contour surface of pupil data.

ppl_prep_data

Check the classes of specific columns and re-assigns as necessary.

ppl_rm_extra_DVcols

Checks for and removes unnecessary DV output columns.

ppl_select_recorded_eye

Select the eye used during recording

PupilPre

PupilPre: Preprocessing Pupil Size Data.

recode_off_screen

Check for samples off-screen and marks as NA.

rm_sparse_events

Removes events with excessive missing data

trim_filtered

Trim the beginning and end of filtered events.

user_cleanup_app

Interactive app for manually cleaning pupil data.

verify_cleanup_app

Interactive app for verifying auto cleanup.

Pupillometric data collected using SR Research Eyelink eye trackers requires significant preprocessing. This package contains functions for preparing pupil dilation data for visualization and statistical analysis. Specifically, it provides a pipeline of functions which aid in data validation, the removal of blinks/artifacts, downsampling, and baselining, among others. Additionally, plotting functions for creating grand average and conditional average plots are provided. See the vignette for samples of the functionality. The package is designed for handling data collected with SR Research Eyelink eye trackers using Sample Reports created in SR Research Data Viewer.

  • Maintainer: Aki-Juhani Kyröläinen
  • License: GPL-3
  • Last published: 2020-03-10