replaces missing observations if you have some degree of incomplete observations

This is a useful function if you have a dataset where certain timepoints have been removed for whatever reason, but you want continuous time data. This will make assumptions about trials being the same length though, so may not be appropriate for all data types. This should only be run after running make_pupillometry_data.

replace_missing_data(data)

Arguments

data

your data of class pupillometryR

Value

A time-stepped data frame

Examples

data(pupil_data)
Sdata <- make_pupillometryr_data(data = pupil_data,
subject = ID,
trial = Trial,
time = Time,
condition = Type)
new_data <- replace_missing_data(data = Sdata)
#> replace_missing_data will only help if you have missing timepoints, and a reliable time column.