Here we describe (1) how to calculate the correlation coefficient from a study that is reported in considerable detail and (2) how to impute a change-from-baseline standard deviation in another study, making use of an imputed correlation coefficient. A typically unreported number known as the correlation coefficient describes how similar the baseline and final measurements were across participants. The following alternative technique may be used for imputing missing standard deviations for changes from baseline (Follmann 1992, Abrams 2005). However, the appropriateness of using a standard deviation from another study relies on whether the studies used the same measurement scale, had the same degree of measurement error and had the same time periods (between baseline and final value measurement). When change-from-baseline standard deviations for the same outcome measure are available from other studies in the review, it may be reasonable to use these in place of the missing standard deviations. When there is not enough information available to calculate the standard deviations for the changes, they can be imputed. confidence intervals, standard errors, t values, P values, F values) then the techniques described in Chapter 7 (Section 7.7.3) may be used. If statistical analyses comparing the changes themselves are presented (e.g. Some other information in a paper may help us determine the standard deviation of the changes. We cannot know whether the changes were very consistent or very variable. However, the information in this table does not allow us to calculate the standard deviation of the changes. Note that the mean change in each group can always be obtained by subtracting the final mean from the baseline mean even if it is not presented explicitly.