estimateShuffle estimates the following quantities for a response vector:
the signal variance (signalVar), the noise variance (noiseVar), the total variance (YVar),
and the explainable variance (effect). Inputs to the function are the response vector, and
a preprocessing structure (the output of prepareShuffle) which holds the design, the shuffle permutation, and
the calculated normalizer.
Usage
estimateShuffle(dat, prep, neg = FALSE)
Arguments
dat
A vector of reponses - should be of the same size as the design vector and the shuffle permutation.
prep
The output of prepareShuffle; includes the design, the shuffling permuation, and a normalizer.
neg
If neg=FALSE does not allow the signal variance to get arbitrary negative values,
but instead sets signal variance to -1e-05.
Value
signalVar
The estimated variance of the signal
noiseVar
The estimated variance of the noise
YVar
The estimated total variance
effect
The proportion of explainable variance (signalVar/Yvar)
Details
estimateShuffle compares the mean-square-between of the data
to the mean-square-between of the permuted data, the difference being the scaled noise variance.
Effect size is the ratio between the estimated signal data and the estimated total variance.
References
Benjamini and Yu (2013), "The shuffle estimator for explainable variance in fMRI experiments".