plot_tete: Routine Visualization of ERP data

In PsyChiLin/ggerp: Graphical exploration of ERP data

Description

This fucntion generates routine visualization of individual or summarized ERP curves for selected channels conditioned on a factor variable with or without a grouping variable.

Usage

plot_tete(data, frames = NULL, uV, subject = NULL, channel = NULL,
  test = NULL, mode = c("raw", "mean", "bootci"), order = F,
  curve.col = NULL, labs = list(x = "Time (ms)", y =
  "Amplitude (microvolt)"), ggtheme = NULL, scalp = FALSE,
  coord.mat = NULL, ylim = c(-20, 20), curve.fun = function(x, d) {    
  return(mean(x[d])) }, boot.num = 200, boot.intval = c(0.025, 0.975),
  ci.alpha = 0.3)

Arguments

data	a data frame with ERP data
frames	The time point of the ERP data
uV	The corresponding column indices within the input data frame for the ERP amplitudes
subject	The corresponding column index for the subject variables (factor)
channel	The corresponding column index for the channel variables (factor)
test	The corresponding column index for the variables you want to compare. It could be a factor (i.e, Condition) or numeric variable (i.e, Score).
mode	The options ("raw","mean","bootci") of the functions control the kind of plots to be made.
order	Reordering the plots by the similarities between the curves using TSclust package.
curve.col	The color for the curves. Numbers must match. (e.g. two conditions need two colors)
labs	The labs of the plot
ggtheme	The theme setting for ggplot2
scalp	Logical variable. Plot the curve on the scalp location (follow the coord.mat option).
coord.mat	Read users' own coordinate matrix. Default is the full 10/10 system.
ylim	The limits of the plot on Y axis. The setting is same for ggplot2.
curve.fun	The function you want to aggreagate when model == mean or bootci. For example, curve.fun = function(x, d)return(mean(x[d])). See boot for further information.
boot.num	The number of bootstrap replicates (when mode == bootci). Usually this will be a single positive integer (Default is 200).
boot.intval	A scalar or vector containing the confidence levels (when mode == bootci), i.e, boot.intval = c(0.025,0.975).
ci.alpha	The alpha value (the ggplot2 setting) for the ribbon area of the confidence interval (when mode == bootci).

Author(s)

Chi-Lin Yu <[e-mail]>, Ching-Fan Sheu <[e-mail]>

See Also

plot_fa plot_coord

Examples

data(DirectedForgetting)
time_pt <- seq(-200, 1000, 1)

plot_tete(data = DirectedForgetting, 
          frames = time_pt, 
          channel = 5, subject = 1, uV = 6:1206, test = 4,
          mode = "mean", scalp = TRUE)

dta_c <- filter(DirectedForgetting, 
                Channel %in% c("FZ", "FCZ", "CZ", "PZ")) 
                %>% droplevels()
plot_tete(data = dta_c, 
          frmaes = time_pt, 
          channel = 5, subject = 1, uV = 6:1206, test = 4,
          mode = "raw")

dta_c <- filter(DirectedForgetting, 
                Channel == "CZ" ) 
                %>% droplevels()
plot_tete(data = dta_c, 
          frames = time_pt, 
          channel = 5, subject = 1, uV = 6:1206, test = 4,
          mode = "bootci")

PsyChiLin/ggerp documentation built on May 16, 2019, 2:28 a.m.