ppcor: An R Package for a Fast Calculation to Semi-partial Correlation Coefficients
Author(s) -
Seong Ho Kim
Publication year - 2015
Publication title -
communications for statistical applications and methods
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.326
H-Index - 6
eISSN - 2383-4757
pISSN - 2287-7843
DOI - 10.5351/csam.2015.22.6.665
Subject(s) - partial correlation , mathematics , correlation , computation , statistic , correlation coefficient , matrix (chemical analysis) , test statistic , fisher transformation , statistics , statistical hypothesis testing , algorithm , materials science , geometry , composite material
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.
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