Why should we report the correlation coefficient or the variance of the score differences in "before-after" intervention studies when the dependent variable is continuous?

Dear Editor, Sample size calculation is one of the most important steps in developing a plan for research projects/dissertations. The sample size affects the power of the study and also has economic implications for a research project. If the sample size would be less than the required level, the tests used to analyze the research data will not have adequate power. Also, if the sample size would be too many, it will cause a waste of resources. In this regard, it is suggested that researchers report the "correlation coefficient between the data before and after the intervention" in addition to the mean and standard deviation in a pre-and post-intervention study with a quantitative dependent variable so that other researchers can refer to it and calculate the sample size of their study correctly.