I am doing a research project on the topic of replicability in psychology. To do this, I did a set of 10 meta-analysis on different studies.
My problem is the following : some of those studies were between subject but most were within subject. To calculate the effect sizes in those studies, I believe I need to know the correlation between the two measures. However, most studies do not report any correlation, and since I do not have access to the original datasets (some studies are more than 15 years old), it is not possible for me to retrieve them. When looking for a solution on the Internet, I have been finding conflicting answers : - should I just ignore the correlation, as this article seems to suggest it ? (http://jakewestfall.org/blog/index.php/2016/03/25/five-different-cohens-d-statistics-for-within-subject-designs/) - should I use a random correlation ? - Or try to find a median correlation in the field ? (If so, how ?) - Should I do something else ?
I am hoping that I am not the first one to be in such a predicament and that some one more well-versed in statistics than me (a Philosophy major) might be able to provide some insight on this issue. In any case, I am very grateful to any one reading and commenting on this post !