摘要
The primary aim of clinical trials is to investigate whether a treatment is effective for a particular disease or condition. Randomized controlled clinical trials are considered to be the gold standard for evaluating the effect of a certain intervention. However, in clinical trials, even after randomization, there are situations where the patients differ substantially with respect to the baseline value of the outcome variable. Many a times the response to interventions depends on the baseline values of the outcome variable. When there are baseline-dependent treatment effects, differences among treatments vary as a function of baseline level. Although variation in outcome associated with baseline value is accounted for in ANCOVA, analysis of individual differences in treatment effect is precluded by the homogeneity of regression assumption. This assumption requires that expected differences in outcome among treatments be constant across all baseline levels. To overcome this difficulty, Weigel and Narvaez [7] proposed a regression model for two treatment groups to analyze individual response to treatments in randomized controlled clinical trials. The authors reviewed the model suggested by Weigel and Narvaez and extended further for three or more treatment groups. The utility of the model was demonstrated with real life data from a randomized controlled clinical trial of bronchial asthma.
