Our aim in this course is to provide participants with the ability to analyse their own data using multiple imputation, but also to be aware of the pitfalls and limitations of the technique.

This course builds on a basic course in sample-size calculations such as the one provided by the ICH, and provides an overview of the underlying statistical theory for sample size calculations within the hypothesis testing framework. It addresses practical issues and statistical considerations when calculating sample sizes for a wide range of advanced trial designs and outcome distributions, including factorial, non-inferiority, DURATIONS, group sequential, and clustered randomised clinical trials. It uses real advanced trial examples to calculate the sample size using the available user-written software in both R and Stata. 

Those working on trials and study designs, which includes trialists, trial statisticians, clinicians and other scientists. Familiarity with the hypothesis testing framework (i.e., type I error rate, power, and various effect sizes) are essential. Familiarity with sample size calculation for simple/basic designs is desirable but not essential.

Simulation studies are an important tool for statistical research. They help us understand the properties of statistical methods and compare different methods. To perform a meaningful simulation study, careful thought needs to be put into the planning, coding, analysis and interpretation. Participants are expected to attend all sessions but course materials will be available in case of unexpected missed sessions.