Repeated measurements are often collected over time to evaluate treatment efficacy in clinical trials. Most of the statistical models of the repeated measurements have been focusing on their mean response as function of time. These models usually assume that the treatment has persistent effect of constant additivity or multiplicity on the mean response functions throughout the observation period of time. In reality, however, such assumption may be confounded by the potential existence of the so-called effectiveness action onset, although they are often unobserved or difficult to obtain. Instead of including nonparametric time-varying coefficients in the mean response models, we propose and study some semiparametric mean response models to accommodate such effectiveness times. Our methodologies will be demonstrated by a real randomised clinical trial data.


Clinical Trials | Longitudinal Data Analysis and Time Series | Statistical Models