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Often abbreviated DID or DD, this is a technique for inferring causality from observational data. It involves comparing measurements before and after a treatment occurs (hence, the growth rate) in both a group that received the treatment, and an otherwise comparable group that did not.

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Meta-analysis for studies with both baseline and follow-up measurements in both control and ...

I am new to meta-analysis. I did a quick search, and I think I can wrap my mind around generating cohen's d and its variance when there is only a single distribution for each of the control group (C) …
Matthew Hui's user avatar