2004Journal of Chromatographic ScienceRequires access

A New Method to Evaluate the Similarity of Chromatographic Fingerprints: Weighted Pearson Product-Moment Correlation Coefficient

Ying Liu, Qiong Meng, Rui Chen, Jingjing Wang, S. Jiang, Yongmei Hu

Open publisher page 27 citations

Abstract

The Pearson product-moment correlation coefficient is being used to evaluate the similarity of the high-performance liquid chromatographic fingerprints of traditional Chinese medicine (TCM) in China. It is confirmed that a large range of peak areas produced the wrong results. A new algorithm concerning weighted Pearson product-moment correlation coefficient is proposed in this article. The results for both real cases and simulated data sets show that the weighted Pearson product-moment correlation coefficients allow relatively larger differences for large values, smaller differences for small values, and more reliable results than the unweighted Pearson product-moment correlation coefficients. Weight selection depends on the specific scientific problem.

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What this paper is about

The Pearson product-moment correlation coefficient is being used to evaluate the similarity of the high-performance liquid chromatographic fingerprints of traditional Chinese medicine (TCM) in China. It is confirmed that a large range of peak areas produced the wrong results. A new algorithm concerning weighted Pearson product-moment correlation coefficient is proposed in this article. The results for both real cases and simulated data sets show that the weighted Pearson product-moment correlation coefficients allow relatively larger differences for large values, smaller differences for small values, and more reliable results than the unweighted Pearson product-moment correlation coefficients. Weight selection depends on the specific scientific problem.

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OpenAlex reports 27 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

The Pearson product-moment correlation coefficient is being used to evaluate the similarity of the high-performance liquid chromatographic fingerprints of traditional Chinese medicine (TCM) in China. It is confirmed that a large range of peak areas produced the wrong results. A new algorithm concerning weighted Pearson product-moment correlation coefficient is proposed in this article. The results for both real cases and simulated data sets show that the weighted Pearson product-moment correlation coefficients allow relatively larger differences for large values, smaller differences for small values, and more reliable results than the unweighted Pearson product-moment correlation coefficients. Weight selection depends on the specific scientific problem.

Key concepts: Pearson product-moment correlation coefficient, Correlation coefficient, Similarity (geometry), Moment (physics), Correlation, Statistics, Mathematics, Product (mathematics)

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