The two-trials rule requires "at least two adequate and well-controlled studies, each convincing on its own, to establish effectiveness". This is usually employed by requiring two significant studies and is the standard requirement by regulators before new drugs are approved. Recently some generaliziations and alternatives have been proposed, among them the harmonic mean chi-squared test for two or more studies (Held, 2020, doi: 10.1111/rssc.12410) and the 2-of-3 rule (Rosenkranz, 2022, doi: 10.1007/s43441-022-00471-4). The goal of this Master thesis is to compare the different approaches in terms of their error rates and expected sample sizes in a simulation study and to investigate the applicability of a new method based on recent developments described in Micheloud et al (2023, https://arxiv.org/abs/2207.00464). The work is ideal for a Master student with interest pharmaceutical/regulatory statistics and some expertise in implementing statistical methods in R packages and planning and conducting a large-scale simulation study.

Traditional power calculations are based on standard point null hypothesis testing. However, in practice it is often more important to quantify the evidence for a clinically relevant effect rather than for a non-zero effect. The project will investigate the literature on this topic with special attention to the design and analysis of preclinical replication studies.