Analyses total time on defined AOI regions across trials. Works with fixation and raw data as the input (must use one or the other, not both).
Usage
AOI_time(
data,
data_type = NULL,
AOIs,
AOI_names = NULL,
sample_rate = NULL,
as_prop = FALSE,
trial_time = NULL
)Arguments
- data
A dataframe of either fixation data (from fix_dispersion) or raw data
- data_type
Whether data is a fixation ("fix") or raw data ("raw")
- AOIs
A dataframe of areas of interest (AOIs), with one row per AOI (x, y, width_radius, height).
- AOI_names
An optional vector of AOI names to replace the default "AOI_1", "AOI_2", etc.
- sample_rate
Optional sample rate of the eye-tracker (Hz) for use with data. If not supplied, the sample rate will be estimated from the time column and the number of samples.
- as_prop
whether to return time in AOI as a proportion of the total time of trial
- trial_time
needed if as_prop is set to TRUE. a vector of the time taken in each trial. Equal to the length of x trials by y participants in the dataset
Value
a dataframe containing the time on the passed AOIs for each trial. One column for each AOI separated by trial.
Details
Analyses data separately for each unique combination of values in pID and trial. Returned values can be absolute time or proportion of time over the period.
Examples
# \donttest{
data <- combine_eyes(HCL)
fix_d <- fixation_dispersion(data)
# fixation data
AOI_time(data = fix_d, data_type = "fix", AOIs = HCL_AOIs)
#> pID trial AOI time
#> 1 118 1 AOI_1 3500
#> 2 118 2 AOI_1 1400
#> 3 118 3 AOI_1 576
#> 4 118 4 AOI_1 2563
#> 5 118 5 AOI_1 253
#> 6 118 6 AOI_1 789
#> 7 118 1 AOI_2 1598
#> 8 118 2 AOI_2 1292
#> 9 118 3 AOI_2 743
#> 10 118 4 AOI_2 3574
#> 11 118 5 AOI_2 1101
#> 12 118 6 AOI_2 909
#> 13 118 1 AOI_3 6056
#> 14 118 2 AOI_3 3924
#> 15 118 3 AOI_3 2932
#> 16 118 4 AOI_3 2609
#> 17 118 5 AOI_3 2136
#> 18 118 6 AOI_3 2564
#> 19 119 1 AOI_1 3656
#> 20 119 2 AOI_1 912
#> 21 119 3 AOI_1 1959
#> 22 119 4 AOI_1 4288
#> 23 119 5 AOI_1 4805
#> 24 119 6 AOI_1 3447
#> 25 119 1 AOI_2 1743
#> 26 119 2 AOI_2 880
#> 27 119 3 AOI_2 2152
#> 28 119 4 AOI_2 2043
#> 29 119 5 AOI_2 3270
#> 30 119 6 AOI_2 2920
#> 31 119 1 AOI_3 2740
#> 32 119 2 AOI_3 1944
#> 33 119 3 AOI_3 2106
#> 34 119 4 AOI_3 1686
#> 35 119 5 AOI_3 2983
#> 36 119 6 AOI_3 4962
#raw data
AOI_time(data = data, data_type = "raw", AOIs = HCL_AOIs)
#> pID trial AOI time
#> 1 118 1 AOI_1 3663
#> 2 118 2 AOI_1 1420
#> 3 118 3 AOI_1 593
#> 4 118 4 AOI_1 2579
#> 5 118 5 AOI_1 370
#> 6 118 6 AOI_1 817
#> 7 118 1 AOI_2 1723
#> 8 118 2 AOI_2 1373
#> 9 118 3 AOI_2 797
#> 10 118 4 AOI_2 3783
#> 11 118 5 AOI_2 1160
#> 12 118 6 AOI_2 926
#> 13 118 1 AOI_3 6199
#> 14 118 2 AOI_3 4179
#> 15 118 3 AOI_3 3090
#> 16 118 4 AOI_3 2903
#> 17 118 5 AOI_3 2349
#> 18 118 6 AOI_3 2916
#> 19 119 1 AOI_1 3926
#> 20 119 2 AOI_1 953
#> 21 119 3 AOI_1 2020
#> 22 119 4 AOI_1 4376
#> 23 119 5 AOI_1 5066
#> 24 119 6 AOI_1 3513
#> 25 119 1 AOI_2 1813
#> 26 119 2 AOI_2 1047
#> 27 119 3 AOI_2 2333
#> 28 119 4 AOI_2 2120
#> 29 119 5 AOI_2 3723
#> 30 119 6 AOI_2 3153
#> 31 119 1 AOI_3 2816
#> 32 119 2 AOI_3 2166
#> 33 119 3 AOI_3 2410
#> 34 119 4 AOI_3 1770
#> 35 119 5 AOI_3 3183
#> 36 119 6 AOI_3 5056
#as proportional data
AOI_time(data = fix_d, data_type = "fix", AOIs = HCL_AOIs,
as_prop = TRUE, trial_time = HCL_behavioural$RT)
#> pID trial AOI time
#> 1 118 1 AOI_1 0.25993316
#> 2 118 1 AOI_2 0.11867805
#> 3 118 1 AOI_3 0.44975863
#> 4 118 2 AOI_1 0.17958618
#> 5 118 2 AOI_2 0.16573239
#> 6 118 2 AOI_3 0.50335441
#> 7 118 3 AOI_1 0.10936432
#> 8 118 3 AOI_2 0.14107238
#> 9 118 3 AOI_3 0.55669477
#> 10 118 4 AOI_1 0.25859894
#> 11 118 4 AOI_2 0.36060579
#> 12 118 4 AOI_3 0.26324021
#> 13 118 5 AOI_1 0.05718548
#> 14 118 5 AOI_2 0.24885855
#> 15 118 5 AOI_3 0.48279915
#> 16 118 6 AOI_1 0.15102791
#> 17 118 6 AOI_2 0.17399793
#> 18 118 6 AOI_3 0.49079285
#> 19 119 1 AOI_1 0.35980711
#> 20 119 1 AOI_2 0.17153823
#> 21 119 1 AOI_3 0.26965850
#> 22 119 2 AOI_1 0.17986747
#> 23 119 2 AOI_2 0.17355633
#> 24 119 2 AOI_3 0.38340170
#> 25 119 3 AOI_1 0.25872657
#> 26 119 3 AOI_2 0.28421623
#> 27 119 3 AOI_3 0.27814097
#> 28 119 4 AOI_1 0.47366037
#> 29 119 4 AOI_2 0.22567354
#> 30 119 4 AOI_3 0.18623866
#> 31 119 5 AOI_1 0.37422118
#> 32 119 5 AOI_2 0.25467290
#> 33 119 5 AOI_3 0.23232087
#> 34 119 6 AOI_1 0.27193121
#> 35 119 6 AOI_2 0.23035658
#> 36 119 6 AOI_3 0.39144841
# }