Calculation for the Test of the Difference
Between Two Dependent Correlations
with One Variable in Common

quantpsy.org

© 2010-2025,
Kristopher J. Preacher

Calculation for the test of the difference between two dependent correlations with one variable in common
Ihno A. Lee (Stanford University)
Kristopher J. Preacher (Vanderbilt University)

How to cite this page

This web utility may be cited in APA style in the following manner:

Lee, I. A., & Preacher, K. J. (2013, September). Calculation for the test of the difference between two dependent correlations with one variable in common [Computer software]. Available from http://quantpsy.org.

The purpose of this page

This interactive calculator yields the result of a test of the equality of two correlation coefficients obtained from the same sample, with the two correlations sharing one variable in common. The result is a z-score which may be compared in a 1-tailed or 2-tailed fashion to the unit normal distribution. By convention, values greater than |1.96| are considered significant if a 2-tailed test is performed.

How it's done

First, each correlation coefficient is converted into a z-score using Fisher's r-to-z transformation. Then, we make use of Steiger's (1980) Equations 3 and 10 to compute the asymptotic covariance of the estimates. These quantities are used in an asymptotic z-test.

How to use this page

Enter the two correlation coefficients to be compared (r_jk and r_jh), along with the correlation of the unshared variables (r_kh) and the sample size, into the boxes below. Then click on "calculate." The p-values associated with both a 1-tailed and 2-tailed test will be displayed in the "p" boxes.

r n Output: rjk: z-score: rjh: 1-tail p: rkh: 2-tail p: Status:

References

Steiger, J. H. (1980). Tests for comparing elements of a correlation matrix. Psychological Bulletin, 87, 245-251.

Acknowledgments

Original version posted September, 2013. Free JavaScripts provided by The JavaScript Source and John C. Pezzullo.