Description Usage Arguments Value Author(s) See Also Examples
the function plot fa performs factor-adjusted multiple testing of ERP curves in the linear model framework (Causeur et al, 2012) and display results the same way as that of plot_tete
.
1 2 3 4 5 6 | plot_fa(data, frames = NULL, uV, subject = NULL, channel = NULL,
test = NULL, mode = c("test", "test_signal"), curve.col = NULL,
labs = list(x = "Time (ms)", y = "Amplitude (microvolt)"), ggtheme = NULL,
order = F, scalp = FALSE, coord.mat = NULL, ylim = c(-20, 20),
significant.col = "darkgoldenrod", significant.alpha = 0.1,
design = NULL, design0 = NULL, ...)
|
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 ("test","test_signal") of the functions control the kind of plots to be made. |
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 |
order |
Reordering the plots by the similarities between the curves using TSclust package. |
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. |
significant.col |
The color used to indicated the significant time point. |
significant.alpha |
The alpha of the significant.col that used to indicated the significant time point. |
design |
Design matrix of the full model for the relationship between the ERP and the experimental variables. Typically the output of the function model.matrix (see the R package Causeur, David, Ching-Fan Sheu, and Mei-Chen Chu. "Significance analysis of ERP data." (2014).) |
design0 |
Design matrix of the null model. Typically a submodel of the full model, obtained by removing columns from design. Default is NULL, corresponding to the model with no covariates. (see the R package Causeur, David, Ching-Fan Sheu, and Mei-Chen Chu. "Significance analysis of ERP data." (2014).) |
... |
Other parameters in |
Plot A "ggplot2" plot will automatically generate.
Test_Rst A same testing results of erpfatest
.
Chi-Lin Yu <psychilinyu@gmail.com>, Ching-Fan Sheu <csheu@mail.ncku.edu.tw>
plot_tete
plot_coord
erpfatest
1 2 3 4 5 6 7 8 9 10 11 12 | data(DirectedForgetting)
time_pt <- seq(-200, 1000, 1)
dta_c <- DirectedForgetting %>%
filter(Channel %in% c("FZ","CZ","PZ")) %>%
droplevels()
plot_fa(data = dta_c,
frames = time_pt,
channel = 5, subject = 1, uV = 6:1206, test = 4,
mode = "test_signal",
design = (~Subject + Condition), design0 = (~Subject), nbf = 5)
|
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