ERP (version 1.0.1)

erpavetest: Significance testing of averaged ERPs. The entire ERP recording time is first partitioned into a pre-determined number of equal intervals. The averaged ERPs for each time intervals are the input for analysis.

Description

The function first calculates averaged ERP values within a predetermined number of equally-spaced intervals then tests for significance of the relationship between averaged ERPs and covariates in a linear model framework.

Usage

erpavetest(dta, design, design0 = NULL, nintervals = 10, method = "none", alpha = 0.05)

Arguments

dta

Data frame containing the ERP curves: each column corresponds to a time frame and each row to a curve.

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

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.

nintervals

Number of intervals in the partition of the whole interval of observation. Default is 10.

method

FDR- or FWER- controlling multiple testing procedures as available in the function p.adjust. Default is "none".

alpha

The FDR or FWER control level. Default is 0.05

Value

• pval
  p-values of the tests.
• correctedpval
  Corrected p-values, for the multiplicity of tests. Depends on the multiple testing method (see function p.adjust).
• significant
  Indices of the time points for which the test is positive.
• segments
  Factor giving the membership of timepoints to each interval in the partition.
• breaks
  Breakpoints of the partition.
• test
  F-statistics.
• df1
  Residual degrees of freedom for the full model.
• df0
  Residual degrees of freedom for the null model.
• signal
  Estimated signal: a pxT matrix, where p is the difference between the numbers of parameters in the full and null models and T the number of frames.
• r2
  R-squared values for each of the T linear models.

See Also

erptest, erpfatest, gbtest, p.adjust, pval.estimate.eta0

Examples

require(mnormt)
require(fdrtool)

data(erpcz)
data(simerp)

# Paired t-tests for the comparison of ERP curves between two groups

tests = erpavetest(erpcz[,1:251],design=model.matrix(~Subject+Instruction,data=erpcz),
   design0=model.matrix(~Subject,data=erpcz))

frames = seq(0,1001,4)
plot(frames,tests$signal,type="l",xlab="Time (ms)",ylab="Difference ERP curves")
points(frames[tests$significant],rep(0,length(tests$significant)),pch=16,col="blue")
abline(v=frames[tests$breaks],lty=2,col="darkgray")
title("Paired comparison at electrode CZ")

# Tests for significance of correlations

tests = erpavetest(simerp[,1:251],design=model.matrix(~y,data=simerp))

plot(frames,sign(tests$signal)*sqrt(tests$r2),type="l",
   xlab="Time (ms)",ylab="Correlation",ylim=c(-1,1))
points(frames[tests$significant],rep(-1,length(tests$significant)),
   pch=16,col="blue")
abline(v=frames[tests$breaks],lty=2,col="darkgray")
title("Simulation")