Adjusting for regression effect in uncontrolled studies.
When clinical studies require enrolled patients to have abnormal assays, the natural tendency of repeat measurements to regress toward the mean can lead to a false assessment of effectiveness of therapy. We propose a method to more accurately estimate the true effect of therapy by adjusting for a component of improvement that can be attributed to regression effect. The model we use allows for a combination of additive and/or multiplicative effects of the therapy.
Department of Mathematics and Statistics, Western Michigan University, Kalamazoo 49008, USA.
J D
JD
Naranjo
J W
JW
McKean
D001699:Biometry; D002784:Cholesterol / Q000097:blood; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D016001:Confidence Intervals; D006801:Humans; D006937:Hypercholesterolemia / Q000097:blood / Q000188:drug therapy; D015233:Models, Statistical; D009010:Monte Carlo Method; D016032:Randomized Controlled Trials as Topic / Q000706:statistics & numerical data; D012044:Regression Analysis; D016896:Treatment Outcome
D002784:Cholesterol