clean_missing_data: Clean missing data above an acceptable threshold

In PupillometryR: A Unified Pipeline for Pupillometry Data

Clean missing data above an acceptable threshold

Description

This function can be used to remove trials and participants who do not meet the threshold for a study. Note that there are two parameters for cleaning, one to remove trials above a threshold, the second to remove participants who drop more than a certain amount of trials.

Usage

clean_missing_data(
  data,
  pupil,
  trial_threshold = 1,
  subject_trial_threshold = 1
)

Arguments

data	your data of class PupillometryR
pupil	a column name denoting pupil size
trial_threshold	a proportion of missing data over which a trial can be considered lost
subject_trial_threshold	a proportion of missing trials over which a participant can be considered lost.

Value

A cleaned PupillometryR dataframe

Examples

data(pupil_data)
Sdata <- make_pupillometryr_data(data = pupil_data,
subject = ID,
trial = Trial,
time = Time,
condition = Type)
new_data <- downsample_time_data(data = Sdata,
pupil = LPupil,
timebin_size = 50,
option = 'mean')
calculate_missing_data(data = new_data, pupil = LPupil)

PupillometryR documentation built on Sept. 15, 2023, 5:13 p.m.