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Updated: Jul 25, 2026

Basics of Multivariate Analysis in Neuroimaging Data
Published on: July 24, 2010
Improved computation of the standard error in the regression coefficient estimates of a multivariate calibration
Abstract:
A multivariate calibration model consists of regression coefficient estimates whose significance depends on the associated standard errors. A recently introduced leave-one-out (LOO) method for computing these standard errors is modified to achieve consistency with the jack-knife method. The proposed modification amounts to multiplying the LOO standard errors with the factor (n - 1)/n1/2, where n denotes the number of calibration samples. The potential improvement for realistic values of n is illustrated using a practical example.
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