Communications for Statistical Applications and Methods · 2015 · 1.2K citations · 18 references
Natural SciencesBiostatisticsComputer SciencePsychometricsStatistical ComputingStatistical ModelingAutocorrelation AnalysisComputational StatisticsCorrelational ResearchMultivariate AnalysisCorrelationCorrelation AnalysisCorrelation MatrixCorrelation Matrix EstimationRecursive EstimationStatistical Significance TestingTest Statistic
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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