Statistical & Practical Aspects of the Design/Analysis of Multi-Arm Multi-Stage Platform Trials.

This half-day workshop consists of two main sessions. The first session of the workshop provides an overview of the design issues involved in MAMS platform protocols. The second session focuses on the implementation of the statistical aspects of such trials and provides guidelines on the design and analysis of such trials. It will also explore further design issues such as adding new research arms, and designs in which research arms are ranked and selectively chosen to continue.

Please note that this course is Online via Zoom.

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:

£124 for attendees from Low Middle Income Countries (LMIC)

£237 Academics/attendees from not-for-profit organisations

£309 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.