plot.time_sequence_data {eyetrackingR}

Plot time-sequence data

Description

Plot the timecourse of looking. Each AOI will be plotted in a separate pane, and data can be split into groups by a predictor column. Data is collapsed by subject for plotting. Supports overlaying the predictions of a growth-curve mixed effects model on the data

Usage

## S3 method for class 'time_sequence_data'
plot(x, predictor_column = NULL, dv = "Prop",
  model = NULL, ...)

Arguments

`x`	Your data from `make_time_sequence_data`. Will be collapsed by subject for plotting (unless already collapsed by some other factor).
`predictor_column`	Data can be grouped by a predictor column (median split is performed if numeric)
`dv`	What measure of gaze do you want to use? (`Prop`, `Elog`, or `ArcSin`)
`model`	(Optional) A growth-curve mixed effects model (from `lmer`) that was used on the `time_sequence_data`. If model is given, this function will overlay the predictions of that model on the data
`...`	Ignored

Value

A ggplot object

Examples

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
)
response_time <- make_time_sequence_data(data, time_bin_size = 250, 
                                         predictor_columns = c("MCDI_Total"),
                                         aois = "Animate", summarize_by = "ParticipantName")

# visualize time results
plot(response_time, predictor_column = "MCDI_Total")

[Package eyetrackingR version 0.1.3]