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== General == FsFast utility to compute contrasts for testing hypotheses based on a GeneralLinearModel (GLM), including t and F statistics, significances of those statistics, and contrast effects sizes (ces). == Algorithm == All the contrast outputs will be found in sess/analysis/contrast (for native space) or sess/analysis/spacedir/contrast (for resampled). Note: the significances are stored as -log10(p). This program uses a univariate general linear model to compute the contrasts: y = X*b + n where y is the raw data vector, X is the design matrix (the columns of which are regressors), b is the vector of model parameters (regression coefficients), and n noise. The noise is need not be white, but white will be assumed for this discussion. The best estimate of b is bhat = inv(X'*X)*X'*y, with residual variance r = y - X*bhat. The residual variance is rvar = r'r/DOF, where DOF is the number of rows of X minus the number of columns. bhat and rvar are computed by selxavg-sess; both are stored in the h volume. The X matrix can be found in the session-level analysis directory in X.mat. A contrast matrix C is a matrix with number of columns equal to the number of columns in X. The contrast matrix is created by mkcontrast-sess and can be found the the project-level analysis directory (files with .mat). C can have any number of rows J. The contrast effect size (CES) is then ces = C*bhat. The CES is saved in the volume called ces. Note: there is also a volume called cespct which is the CES as a percent of the mean functional value. When J=1 (ie, there is only one row in C), the variance of the ces is cesvar = rvar * (C * inv(X'*X) *C'). A t-statistic is formed by t = ces/sqrt(cesvar), and the significance is computed. The result is stored in volumes called t and sig, respectively. When J>1 (ie, there multiple row in C), several things are done. First, an F-ratio is computed as F = ces'*inv(C*inv(X'*X)*C')*ces/(J*rvar); the signfificance of this ratio is also compued. The result is stored in volumes called f and fsig, respectively. Second, a separate t-test of performed for each row of C as described above; all results are still stored in the t and sig volumes, but these volumes will have J frames. Finally, the best (smallest) significance within the J significances computed at a voxel is stored in minsig (after multiplication by J as a bonferroni correction). The row as which the min sig was found is stored in iminsig. Note: the significances are stored as -log10(p). For t-tests, the signifiance is given the same sign as the t-value. |
Index TableOfContents
Name
stxgrinder-sess - compute contrasts based on GeneralLinearModel
Synopsis
stxgrinder-sess - ??
Arguments
Required Flagged Arguments
??
Optional Flagged Arguments
-a <analysisname> |
session-level functional analysis name |
Analysis as created by ["mkanalysis-sess.new"] and computed by selxavg-sess |
-c <contrast> [<-c contrast>] |
contrasts |
|
-all |
compute all contrasts for given analysis |
|
-space <spacename> |
space in which to average (native, tal, sph) |
|
-spacedir <spacedir> |
space directory (default spacename) |
|
-hemi <hemisphere> |
with sph space <lh rh> |
|
-fdofmax <dofmax> |
max dof for F-test |
|
-sf <sessidfile> |
... |
|
-df <srchdirfile> |
... |
|
-s <sessid> |
... |
|
-d <srchdir> |
... |
|
-help |
|
|
-umask <umask> |
set unix file permission mask |
|
-version |
print version and exit |
Outputs
ces |
Contrast Effect Size = C*bhat |
cespct |
ces expressed as a percentage of mean baseline |
cesvar |
variance of ces |
t |
t-ratio |
sig |
significance based on t-test |
f |
f-ratio (when J>1) |
fsig |
significance based on F-test (when J>1) |
minsig |
best significance, boferroni corrected (when J>1) |
iminsig |
index of best significance (when J>1) |
Description
General
FsFast utility to compute contrasts for testing hypotheses based on a GeneralLinearModel (GLM), including t and F statistics, significances of those statistics, and contrast effects sizes (ces).
Algorithm
All the contrast outputs will be found in sess/analysis/contrast (for native space) or sess/analysis/spacedir/contrast (for resampled). Note: the significances are stored as -log10(p).
This program uses a univariate general linear model to compute the contrasts:
y = X*b + n
where y is the raw data vector, X is the design matrix (the columns of which are regressors), b is the vector of model parameters (regression coefficients), and n noise. The noise is need not be white, but white will be assumed for this discussion.
The best estimate of b is bhat = inv(X'*X)*X'*y, with residual variance r = y - X*bhat. The residual variance is rvar = r'r/DOF, where DOF is the number of rows of X minus the number of columns. bhat and rvar are computed by selxavg-sess; both are stored in the h volume. The X matrix can be found in the session-level analysis directory in X.mat.
A contrast matrix C is a matrix with number of columns equal to the number of columns in X. The contrast matrix is created by mkcontrast-sess and can be found the the project-level analysis directory (files with .mat). C can have any number of rows J. The contrast effect size (CES) is then ces = C*bhat. The CES is saved in the volume called ces. Note: there is also a volume called cespct which is the CES as a percent of the mean functional value.
When J=1 (ie, there is only one row in C), the variance of the ces is cesvar = rvar * (C * inv(X'*X) *C'). A t-statistic is formed by t = ces/sqrt(cesvar), and the significance is computed. The result is stored in volumes called t and sig, respectively.
When J>1 (ie, there multiple row in C), several things are done. First, an F-ratio is computed as F = ces'*inv(C*inv(X'*X)*C')*ces/(J*rvar); the signfificance of this ratio is also compued. The result is stored in volumes called f and fsig, respectively. Second, a separate t-test of performed for each row of C as described above; all results are still stored in the t and sig volumes, but these volumes will have J frames. Finally, the best (smallest) significance within the J significances computed at a voxel is stored in minsig (after multiplication by J as a bonferroni correction). The row as which the min sig was found is stored in iminsig.
Note: the significances are stored as -log10(p). For t-tests, the signifiance is given the same sign as the t-value.
Notes
The significances are stored as -log10(p).
For t-tests, the signifiance is given the same sign as the t-value.
For F-tests, the signifiance is not given a sign. This is the only difference with stxgrinder-sess.
t-test is not saved when contrast is omnibus or zomnibus
An "old" version of stxgrinder-sess is available as ["stxgrinder0-sess"].
Examples
Example 1
??
Example 2
??
Bugs
The program occasionally hangs when performing the F-test. This is caused when the DOF is very large (eg, > 1000). This ofen happens when analyzing group fixed effects. If the program appears to hang, reduce FtestDOFMax with -fdofmax until it seems to run ok. You can also just skip the F-test with -noftest.
See Also
["othercommand1"], ["othercommand2"]
Links
Methods Description
description description
References
["References/Lastname###"]
Reporting Bugs
Report bugs to <analysis-bugs@nmr.mgh.harvard.edu>