# {metafor} variance explaination for paired pre-test/posttest Classic List Threaded 3 messages Open this post in threaded view
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## {metafor} variance explaination for paired pre-test/posttest

 In a previous post https://stat.ethz.ch/pipermail/r-help/2012-April/308946.html, the following calculation was given for imputing the variance of change scores for paired studies: // begin quote 2) Often, the dependent variable is not the same in each study. Then you will have to resort to a standardized outcome measure. There are two options: a) standardization based on the change score standard deviation Then yi = (m1i - m2i) / sdi with sampling variance vi = 1/ni + yi^2 / (2*ni). // end quote I used the sampling variance equation above in a paper that is being reviewed by a coauthor, who is a biostatistician. He commented that he has never seen this equation for variance before, and it looks strange to him. To put my knowledge into perspective, I am an undergraduate taking my first statistics course. I imputed the t-statistic from two-sided p-values reported in the paper, and used that to get the sdi (as in the previous post). I consulted the Cochrane Handbook and The Handbook of Research Syntheses and Meta-analysis 2nd Ed (Cooper, Hedges, Valentine 2009) and couldn't find that equation anywhere. Would Prof. Viechtbauer, or anyone else knowledgeable, mind explaining the sample variance above? I need to be able to defend my choice of equation. Since it's the only method that I found that doesn't rely on a correlation coefficient (which are not included in the papers), I'd like to be able to justify it and not redo calculations for 23 studies if possible. Thank you very much, John ~~~~ John Williams ALB Candidate, Harvard University (Expected May 2014) johnwilliams@fas.harvard.edu jawilliamsjr@gmail.com