In clinical research and development, major or significant protocol amendments of on-going trials may result in a totally different trial, which is unable to address the scientific/medical questions that the original trial intends to answer. Chow, Chang and Pong  examined the impact of protocol amendments on statistical inference assuming a random location shift and a fixed scale shift in the target patient population. In this article, we will focus on the case where there is a fixed location shift but a random scale shift in the target patient population. The impact on the shift in target patient population, statistical inference, and power analysis for sample size adjustment after changes or modifications made to an on-going clinical trial via protocol amendments are studied. Assuming that there is a fixed location shift, an approach taking into consideration of potential random shift in scale parameter as a result of protocol amendment is proposed. Through a simulation study, it shows the proposed method is superior to the classical method by ignoring the shift in patient population in terms of accuracy and reliability for assessment of the treatment effect under study.
Lu, Ying; Chow, Shein-Chung; and Zhang, Zhongzhan, "Statistical Inference for Clinical Trials with Random Shift in Scale Parameter of Target Patient Population" (June 2010). Duke Biostatistics and Bioinformatics (B&B) Working Paper Series. Working Paper 11.