Nothing
## ----results='hide'-----------------------------------------------------------
set.seed(42)
library("Matrix")
library("lme4")
library("ggplot2")
library("eyetrackingR")
data("word_recognition")
data <- make_eyetrackingr_data(word_recognition,
participant_column = "ParticipantName",
trial_column = "Trial",
time_column = "TimeFromTrialOnset",
trackloss_column = "TrackLoss",
aoi_columns = c('Animate','Inanimate'),
treat_non_aoi_looks_as_missing = TRUE
)
## ---- eval=FALSE--------------------------------------------------------------
# animate_aoi <- read.csv("./interest_areas_for_animate_aoi.csv")
#
# # Trial Left Top Right Bottom
# # 1 FamiliarBird 500 100 900 500
# # 2 FamiliarBottle 400 200 800 600
# # 3 FamiliarCow 500 300 900 700
# # 4 FamiliarDog 300 100 700 500
# # 5 FamiliarHorse 500 200 900 600
# # 6 FamiliarSpoon 350 300 750 700
#
# data <- add_aoi(data = data, aoi_dataframe = animate_aoi,
# x_col = "GazeX", y_col = "GazeY",
# aoi_name = "Animate",
# x_min_col = "Left", x_max_col = "Right", y_min_col = "Top", y_max_col = "Bottom")
## -----------------------------------------------------------------------------
table(data$Animate)
table(is.na(data$Animate)) # if all TRUE, then something went wrong.
## ---- echo=FALSE--------------------------------------------------------------
data$Message <- with(data, ifelse(TimeFromTrialOnset==0, "TrialStart", "."))
data$ResponseWindowStart <- 15500
## -----------------------------------------------------------------------------
data <- subset_by_window(data, window_start_msg = "TrialStart", msg_col = "Message", rezero= TRUE)
## -----------------------------------------------------------------------------
response_window <- subset_by_window(data, window_start_col = "ResponseWindowStart", rezero= FALSE, remove= TRUE)
## -----------------------------------------------------------------------------
response_window <- subset_by_window(response_window, window_end_time = 21000, rezero= FALSE, remove= TRUE)
## ---- warning=FALSE-----------------------------------------------------------
# analyze amount of trackloss by subjects and trials
(trackloss <- trackloss_analysis(data = response_window))
response_window_clean <- clean_by_trackloss(data = response_window, trial_prop_thresh = .25)
## ---- warning=FALSE-----------------------------------------------------------
trackloss_clean <- trackloss_analysis(data = response_window_clean)
(trackloss_clean_subjects <- unique(trackloss_clean[, c('ParticipantName','TracklossForParticipant')]))
## ---- warning=FALSE-----------------------------------------------------------
# get mean samples contributed per trials, with SD
mean(1 - trackloss_clean_subjects$TracklossForParticipant)
sd(1- trackloss_clean_subjects$TracklossForParticipant)
## ---- warning=FALSE-----------------------------------------------------------
# look at the NumTrials column
(final_summary <- describe_data(response_window_clean, describe_column = 'Animate', group_columns = 'ParticipantName'))
## ---- warning=FALSE-----------------------------------------------------------
mean(final_summary$NumTrials)
sd(final_summary$NumTrials)
## ---- warning=FALSE-----------------------------------------------------------
response_window_clean$Target <- as.factor( ifelse(test = grepl('(Spoon|Bottle)', response_window_clean$Trial),
yes = 'Inanimate',
no = 'Animate') )
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