Webinar: Dr David Robertson - Unbiased information for adaptive designs

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In adaptive clinical trials, the conventional end-of-trial point estimate of a treatment effect is prone to bias, that is, a systematic tendency to deviate from its true value. While much of the methodological developments on adaptive designs have tended to focus on control of type I error rates and power considerations, in contrast the question of biased estimation has received relatively less attention. Recent regulatory guidance, such as ICH E20, has highlighted the need to use adjusted estimators for adaptive designs to address these issues. In this webinar, we will present an overview of methods for unbiased estimation for adaptive designs. Starting with a systematic review of the methodological literature, we will then focus on the two-stage trial setting, where a variety of minimum variance unbiased estimators have been proposed. We will conclude with some proposed guidelines for researchers around the choice of estimators and the reporting of estimates following an adaptive design.

Speaker:

David Robertson is an Assistant Research Professor at the MRC Biostatistics Unit, University of Cambridge, where he has been based since 2013. His research focuses on the development of novel methodology for the design and analysis of adaptive clinical trials. From 2018 – 2021, David held a Biometrika Trust Research Fellowship, which explored questions around error rate control for clinical trial designs that test multiple hypotheses simultaneously. His current main areas of research include estimation after adaptive designs, response-adaptive randomisation in clinical trials and multiple hypothesis testing.