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How are change scores used to account for difference at baseline?
Change scores are often used to account for differences between groups at baseline. However, they do not control for baseline imbalances between groups. This is because subjects with low scores at baseline tend to improve more than those with high scores, a phenomenon known as regression to the mean.
How is covariance adjusted for differences at baseline?
An analysis of covariance adjusts each subject’s score for their baseline score and is unaffected by chance baseline differences and regression to the mean. This method is easily applied to data at two time points, and assumes linearity between baseline and follow up scores where data are continuous.
When to use a baseline measure in school?
If one of the things your group is planning is an after-school discussion group, then the first indicator would probably be a good one for you to use as a baseline measure, because it should give you a good idea of the numbers of students who might be likely to participate in an after-school activity.
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
Why is it important to test for baseline differences?
Testing for baseline differences is often propagated because of the belief that it shows whether randomization was successful and it identifies real or important differences between treatment arms that should be accounted for in the statistical analyses.
When do you need a difference in difference?
Difference in differences requires data measured from a treatment group and a control group at two or more different time periods, specifically at least one time period before “treatment” and at least one time period after “treatment.”
Is the correlation between baseline and follow up scores high?
If the correlation between baseline and follow up scores is low, using change scores adds variability and consequently, the result is less likely to be significant. If the correlation between baseline and follow up scores is high, the result is more likely to be significant.