- Adaptive Design with Incomplete Paired Data
Mark Chang · 2014
A clinical trial design with paired data often involves missing observations. In such a case, the data from the trial become a mixture of paired and unpaired data. A commonly used approach for the analysis of the trial data is to ignore the incomplete pairs. Such a treatment of missings data is not statistically efficient. We will discuss a simple method that will allow us to use all data, including the incomplete pairs. The method is optimal in the sense that it minimizes the variance. We will show how to design classical and adaptive trials with the proposed method for different types of endpoints with superiority, noninferiority, and equivalence designs. The method can also be used for meta-analysis, in which, some trials are with paired data and some are not.