Calculate the timepoint-by-timepoint mean, standard deviation, standard
error, or variance eeg_epochs objects.
eeg_summarise(data, ...)
# S3 method for class 'eeg_epochs'
eeg_summarise(
data,
statistic = c("sem", "mean", "sd", "var"),
conditions = NULL,
time_lim = NULL,
...
)An eegUtils object.
Various arguments passed to specific functions
The statistic to calculate at each timepoint. Defaults to "sem"
Conditions to group the data by.
Timepoint(s) to summarise. Can be a range, for which a summary statistic will be provided for each timepoint, or a list of individual times. If none is supplied, the function will calculate a summary for every timepoint.
A tibble
eeg_summarise(eeg_epochs): Calculate summary statistics for eeg_epochs
objects
eeg_summarise(demo_spatial, statistic = "sem")
#> # A tibble: 102 × 24
#> time sem_Fp1 sem_Fp2 sem_Fz sem_Cz sem_Pz sem_P3 sem_P4 sem_C3 sem_C4
#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 -0.301 0.0861 0.0769 0.0800 0.0933 0.108 0.0782 0.0879 0.0609 0.0775
#> 2 -0.293 0.0830 0.0763 0.0754 0.0981 0.105 0.0749 0.0837 0.0591 0.0733
#> 3 -0.285 0.0862 0.0733 0.0751 0.100 0.101 0.0737 0.0782 0.0598 0.0688
#> 4 -0.277 0.0907 0.0798 0.0755 0.0989 0.100 0.0730 0.0742 0.0664 0.0675
#> 5 -0.270 0.0885 0.0769 0.0743 0.0913 0.107 0.0726 0.0701 0.0647 0.0660
#> 6 -0.262 0.0857 0.0824 0.0713 0.0894 0.111 0.0795 0.0693 0.0610 0.0679
#> 7 -0.254 0.0860 0.0813 0.0763 0.0916 0.106 0.0859 0.0732 0.0598 0.0760
#> 8 -0.246 0.0877 0.0733 0.0823 0.0914 0.103 0.0823 0.0760 0.0563 0.0833
#> 9 -0.238 0.0835 0.0713 0.0793 0.0877 0.104 0.0730 0.0762 0.0563 0.0867
#> 10 -0.230 0.0847 0.0773 0.0704 0.0821 0.107 0.0739 0.0771 0.0606 0.0818
#> # ℹ 92 more rows
#> # ℹ 14 more variables: sem_P7 <dbl>, sem_P8 <dbl>, sem_F3 <dbl>, sem_F4 <dbl>,
#> # sem_T7 <dbl>, sem_T8 <dbl>, sem_F7 <dbl>, sem_F8 <dbl>, sem_Oz <dbl>,
#> # sem_Fpz <dbl>, sem_EXG1 <dbl>, sem_EXG2 <dbl>, sem_EXG3 <dbl>,
#> # sem_EXG4 <dbl>