robust linear modeling of fmri data
Usage
fmri_rlm(
formula,
block,
baseline_model = NULL,
dataset,
durations,
drop_empty = TRUE,
nchunks = 10,
strategy = c("runwise", "slicewise", "all")
)Arguments
- formula
The model formula for experimental events.
- block
The model formula for block structure.
- baseline_model
(Optional) The
baseline_modelobject. Default is NULL.- dataset
An object derived from
fmri_datasetcontaining the time-series data.- durations
A vector of event durations.
- drop_empty
Whether to remove factor levels with a size of zero. Default is TRUE.
- nchunks
Number of data chunks when strategy is
chunkwise. Default is 10.- strategy
The data splitting strategy, either "runwise" or "chunkwise". Default is "runwise".
Examples
etab <- data.frame(onset=c(1,30,15,25), fac=factor(c("A", "B", "A", "B")), run=c(1,1,2,2))
etab2 <- data.frame(onset=c(1,30,65,75), fac=factor(c("A", "B", "A", "B")), run=c(1,1,1,1))
mat <- matrix(rnorm(100*100), 100,100)
dset <- matrix_dataset(mat, TR=1, run_length=c(50,50),event_table=etab)
dset2 <- matrix_dataset(mat, TR=1, run_length=c(100),event_table=etab2)
#lm.1 <- fmri_rlm(onset ~ hrf(fac), block= ~ run,dataset=dset)
#lm.2 <- fmri_rlm(onset ~ hrf(fac), block= ~ run,dataset=dset2)