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Which is the best method to adjust for baseline?
The overall preferred method is to adjust for baseline and to model the response variable, not computing the change. One reason for this is that change is heavily dependent on getting the transformation of Y correct, and that change does not apply to regression models in general.
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.
When to use baseline score in a RCT?
When using a continuous outcome measure in a randomised controlled trial (RCT), the baseline score should be measured in addition to the post-intervention score, and it should be analysed using the appropriate statistical analysis.
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.
Why are models A and B so different?
Models A and B can produce very different results if the baseline is correlated with the change score (e.g., heavier people have more weight loss), and/or treatment assignment is correlated with the baseline. If you want to know more about these issues, see the cited papers, or here and here.
Is it safe to use percentage change from baseline?
Theoretical considerations suggest that percentage change from baseline will also fail to protect from bias in the case of baseline imbalance and will lead to an excess of trials with non-normally distributed outcome data. Percentage change from baseline should not be used in statistical analysis.
How to analyze change from baseline, absolute or percentage?
From his point of view, one of the advantages of percentage change is that per- centage change is independent of the unit of measurement. For instance, a man who weighs 100 Kg lost 10% of weight after a treatment, i.e. 10 Kg. Equivalently, he lost 22.05 pounds (1Kg = 2:2046 Pounds).