fmri.pvalue {fmri} | R Documentation |
Determine p-values.
fmri.pvalue(spm, mode="basic", delta=NULL, na.rm=FALSE, minimum.signal = 0)
spm |
fmrispm object |
mode |
type of pvalue definition |
delta |
physically meaningful range of latency for HRF |
na.rm |
na.rm specifies how NA's in the SPM are handled. NA's may occur
in voxel where the time series information did not allow for estimating parameters and their variances
or where the time series information where constant over time. A high (1e19) value of the variance
and a parameter of 0 are used to characterize NA's. If na.rm=TRUE the pvalue for the corresponding voxels
is set to 1. Otehrwise pvalues are assigned according to the information found in the SPM at the voxel. |
minimum.signal |
allows to specify a (positive) minimum value for detected signals. If minimum.signal >0 the thresholds are to conservative, this case needs further improvements. |
If only a contrast is given in spm
, we simply use a t-statistic
and define p-values according to random field theory for the resulting gaussian
field (sufficiently large number of df - see ref.). If spm
is a
vector of length larger than one for each voxel, a chisq field is
calculated and evaluated (see
Worsley and Taylor (2006)). If delta
is given, a cone statistics is
used.
The parameter mode
allows for different kinds of p-value
calculation. "basic" corresponds to a global definition of the
resel counts based on the amount of smoothness achieved by an equivalent
Gaussian filter. The propagation condition ensures, that under the
hypothesis
hat{Theta} = 0
adaptive smoothing performs like a non adaptive filter with the same kernel function which justifies this approach. "local" corresponds to a more conservative setting, where the p-value is derived from the estimated local resel counts that has been achieved by adaptive smoothing. In contrast to "basic", "global" takes a global median to adjust for the randomness of the weighting scheme generated by adaptive smoothing. "global" and "local" are more conservative than "basic", that is, they generate sligthly larger p-values.
Object with class attributes "fmripvalue" and "fmridata"
pvalue |
p-value. use with plot for thresholding. |
weights |
voxelsize ratio |
dim |
data dimension |
hrf |
expected BOLD response for contrast (single stimulus only) |
Unexpected side effects may occur if spm does not meet the
requirements, especially if a parameter estimate vector of length greater than 2 through
argument vvector
in fmri.lm
has beeen produced for every voxel.
Karsten Tabelow tabelow@wias-berlin.de
Tabelow, K., Polzehl, J., Voss, H.U., and Spokoiny, V.. Analysing {fMRI} experiments with structure adaptive smoothing procedures, NeuroImage, 33:55-62 (2006).
Worsley, K.J., and Taylor, J.E., Detecting fMRI activation allowing for unknown latency of the hemodynamic response, NeuroImage 29:649-654 (2006).
## Not run: fmri.pvalue(smoothresult)