Using simulation studies to evaluate statistical methods

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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.

Lecturers

Professor Ian White, MRC Clinical Trials Unit at UCL, London
Dr Tim Morris, Novartis, London
Dr Matteo Quartagno, MRC Clinical Trials Unit at UCL, London
Dr Tra My Pham, MRC Clinical Trials Unit at UCL, London

Course Aims

By the end of the course, participants will be able to:

• Explain the rationale for simulation
• Understand the importance of careful planning
• Have the tools to code and debug simple simulation studies in Stata or R
• Know how to analyse simulation studies producing estimates of uncertainty
• Present methods and results for publication

Target audience

• Methodological or applied statisticians who need to evaluate the statistical properties of one or more methods
• PhD students using simulation studies
• Readers of methodology articles which evaluate methods by simulation

Participants should be familiar with Stata or R and know, for example, how to generate data, run a regression command and produce simple graphs.

Software

Practicals can now be undertaken in Stata or R; solutions will be made available for both. Lectures will tend to be about the concepts but where necessary will include specific Stata or R code. Users of other software (e.g. SAS) are welcome but will need to be confident of their proficiency (since the lecturers are not). Attendees will need to bring a laptop with either Stata (version 12 or higher), a recent version of R or a software package of the attendee’s choice installed. Please get in touch with the course organisers if none of these is possible.

Examples

Examples will be taken from the lecturers’ experiences, primarily relating to medical statistics. Principles are the same for simulation studies in other applied areas but the examples may be less relevant.

Fees

The course is likely to be oversubscribed and so if you’re interested in attending then we encourage you to apply early.

This course is free for UCL members of staff within ICTM (Cancer Research UK & UCL Cancer Trials Centre, Comprehensive Clinical Trials Unit at UCL, Medical Research Council Clinical Trials Unit at UCL and PRIMENT Clinical Trials Unit) although places are limited.  Please contact ictm.cpd@ucl.ac.uk for a validation code to make the registration payment. 

Attendees from outside of the ICTM will be required to pay an attendance fee. Fees are based on the attendee’s organisation as follows:

Early Bird Offer:

• £170 - Low Middle Income Countries (LMIC)
• £345 - Academic / attendees from not-for-profit organisations
• £415 - Attendees from for-profit organisations

Standard fees (After 12th April 2026)

• £185 - Low Middle Income Countries (LMIC)
• £370 - Academic / attendees from not-for-profit organisations
• £444 - Attendees from for-profit organisations

Delegates from LMIC Countries

Delegates residing in low middle income countries – Free (Three places – Please contact ictm.cpd@ucl.ac.uk for the validation code).
Once these 3 free places have been filled we offer further LMIC places at a reduced rate of £170 (Please contact ictm.cpd@ucl.ac.uk for the validation code).

For information please contact ictm.cpd@ucl.ac.uk.