Related Experiment Video
Updated: Aug 13, 2026

Evaluation of a Point-of-Care Testing Analyzer for Measuring Peripheral Blood Leukocytes
Published on: March 22, 2022
Comparison of product moment and rank correlation coefficients in the assessment of laboratory method-comparison data
Abstract:
We have studied the effects of range and distribution of data on product moment and rank correlation coefficients when deviation from a linear relationship was due solely to experimentally produced random error. All correlation coefficients (Pearson r, Spearman rho, and Kendall tau) were markedly influenced by the range of the data, and, for the rank correlation coefficients, the effect of range varied for different data distributions. While correlation coefficients may be useful in assessing whether an association exists between two variables, they are not useful in assessing the degree of random error about the regression line when a strong linear association is presumed to exist between the two variables. Thus, neither product moment nor rank correlation coefficients are of value in analysis of laboraoty method-comparison data. The standard deviation of the residual error of regression should be calculated as a measure of the random error about the regression line.
Related Concept Videos
Multiple Comparison Tests
It would be easy to compare two samples using a significance alpha level of 0.05. In other words, there is only one sample pair to be compared. However, it would be difficult to identify a significantly different sample if the number...
Coefficient of Correlation
If you suspect a linear relationship between x and y, then r can measure how strong the linear relationship is.
What the VALUE of r tells us:
The value of r is always between –1 and +1: –1 ≤ r ≤ 1.
The size of the correlation r indicates the strength of the linear...
Calculating and Interpreting the Linear Correlation Coefficient
Spearman's Rank Correlation Test
Spearman's test calculates correlation by...
Calibration Curves: Correlation Coefficient
Correlation and Regression

