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.

Training Course: An Introduction to Design & Analysis of Clinical Trials: Statistics for Non-Statisticians.

This four-day course will provide an introduction to the principles and application of statistics in the randomised controlled trial (RCT) environment. It will explain what's important and why and enable understanding of statistical methods and analyses in RCTs.

Intended audience

Non-statisticians working in clinical trials who only have a basic level of statistical knowledge at present and wish to be more familiar with the meanings of common statistical terms used in clinical trials and the interpretation of results. Generally this course is aimed at people with less than 3 years' experience in a Clinical Trials setting, although all applicants are welcome.

Fees

This course is free for staff from Units within ICTM (CRUK-CTC, CCTU, MRC CTU at UCL and PRIMENT) although places are limited. Places on this course are limited, If demand exceeds the number of places, places will be awarded to those who the course presenters believe will benefit most from the course.Fees are based on the attendee's organisation as follows:

£130 for attendees from Low Middle Income Countries (LMIC)

£245 Academics/attendees from not-for-profit organisations

£320 Attendees from for-profit organisations

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.