ppcor: An R Package for a Fast Calculation to Semi-partial Correlation Coefficients

By Seongho Kim. Communications for Statistical Applications and Methods, 2015

995 citations recorded by the source corpus.

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.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/1f0c9b06cc248b8c91a3bb61dc0693785a8c9be4

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In Molecular Biology

1. Patrick Y. Wu
2. Jonathan Nagler
3. Joshua A. Tucker
4. Solomon Messing

Citations in the corpus

• Large Language Models Can Be Used to Estimate the Latent Positions of Politicians (2023, methodology): “P-values are calculated using the t-statistic described in Kim [28].”