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How to calculate the correlation between baseline and post intervention scores?
The correlation between baseline and post-intervention scores can be derived using the variance sum law. We can then use the derived correlation to calculate the required sample size in the design stage. Baseline imbalance may occur in RCTs, and ANCOVA should be used to adjust for baseline in the analysis stage.
If the treatment is effective the statistical significance of the treatment effect by the two methods will depend on the correlation between baseline and follow up scores. If the correlation is low using the change score will add variation and the follow up score is more likely to show a significant result.
How to adjust for differences at baseline in controlled trials?
A better approach to adjust for differences at baseline is to use an analysis of covariance (ANCOVA) which, in spite of its name, is a type of regression. In an analysis of covariance, follow up scores are plotted against baseline scores and parallel straight lines (linear regression) are fitted through the scores for treatment and control
How does analysing change control for baseline imbalance?
However, analysing change does not control for baseline imbalance because of regression to the mean 1 2 : baseline values are negatively correlated with change because patients with low scores at baseline generally improve more than those with high scores.
How to model pre and post treatment scores?
Instead, if you really want to model both pre- and post-treatment scores, you can use a constrained repeated measure model (time, time*group) by forcing the intercept (or difference in baseline score between two groups) equal to 0. This constrained repeated measure model performs comparably to ANCOVA model.
How is did used to estimate the effect of an intervention?
DID is typically used to estimate the effect of a specific intervention or treatment (such as a passage of law, enactment of policy, or large-scale program implementation) by comparing the changes in outcomes over time between a population that is enrolled in a program (the intervention group) and a population that is not (the control group).
Can a change score be used as an outcome measure?
Using change score as the outcome measure does not address the problem of RTM, nor does it take account of the baseline imbalance. Even if change score is deemed to be the appropriate outcome measure after careful consideration, ANCOVA should still be used to adjust for baseline scores, as shown by Eq. 2.