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Reporting correlations

Correlation analysis—most commonly Pearson correlation analysis—is a valuable statistical technique for establishing 1) whether there is a relationship between variables and the 2) strength of that relationship.

However, there is often confusion on the meaning of the statistical results for such an analysis and the conventional reporting procedures. We aim to correct this confusion.

First, the best possible step is to reference the journal guidelines. Journals where correlation analysis is popular will often specifically state the required reporting measures or reference reporting measures from another organization. In this case, follow these explicit guidelines.

Second, you can adopt the following practice in the absence of any explicit instructions from the journal. These are the elements that must be reported:

Finally, it is wise to include a scatter plot for any correlation analysis. Given that the strength of the relationship is a subjective valuation, the reader should be given an opportunity to gauge the data used to calculate the correlation coefficient. The author should not hide certain data anomalies that might contribute to a statistically significant correlation, such as clustering of data points at the extremes of the relationship. It is also important to include the regression equation generated during the correlation analysis on this plot.

 

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