• Communications for Statistical Applications and Methods
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• 제22권6호
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• pp.665-674
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• 2015

Lack of a general matrix formula hampers implementation of the semi-partial correlation, also known as part correlation, to the higher-order coefficient. This is because the higher-order semi-partial correlation calculation using a recursive formula requires an enormous number of recursive calculations to obtain the correlation coefficients. To resolve this difficulty, we derive a general matrix formula of the semi-partial correlation for fast computation. The semi-partial correlations are then implemented on an R package ppcor along with the partial correlation. Owing to the general matrix formulas, users can readily calculate the coefficients of both partial and semi-partial correlations without computational burden. The package ppcor further provides users with the level of the statistical significance with its test statistic.

• Communications for Statistical Applications and Methods
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• 제29권3호
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• pp.393-396
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• 2022

• Communications for Statistical Applications and Methods
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• 제29권3호
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• pp.397-402
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• 2022

The mathematical expression of the p-value calculation for the semi-partial correlation coefficient differs between Kim (2015) and Cohen et al. (2003). These two expressions were compared and the advantages of Kim (2015)'s approach over Cohen et al. (2003) were discussed.