2020 Statistical Methods for Meta-Analysis of Individual Participant Data (IPD)
Please note: this event has been moved from 30 March - 1 April 2020 to the new dates of 9 - 11 November 2020.
This three-day statistical course provides a detailed foundation of the methods and principles for meta-analysis when IPD (Individual Participant Data) are available from multiple related studies. The course considers continuous, binary and time-to-event outcomes, and covers a variety of modelling options, including fixed effect and random effects. Days 1 and 2 mainly focus on the synthesis of IPD from randomised trials of interventions, where the aim is to summarise a treatment effect or to examine treatment-covariate interactions. We outline how to use either a two-stage framework (day 1) or a one-stage framework (day 2) for the meta-analysis, and compare their pros and cons. Day 3 focuses on novel extensions including multivariate and network meta-analysis of IPD to incorporate correlated and indirect evidence (e.g. from multiple outcomes or multiple treatment comparisons). Special topics will also be covered, including: (i) IPD meta-analysis to identify prognostic/risk factors, (ii) IPD meta-analysis of test accuracy studies; (iii) estimating the power of a planned IPD meta-analysis; and (iv) dealing with unavailable IPD. The course consists of a mixture of lectures and practical sessions to reinforce the underlying statistical concepts. Participants can choose either Stata or R for the practicals. The key messages are illustrated with real examples throughout the course.
The event includes the following:
- The Event includes all the sessions, refreshments and lunches from the 9 - 11 November 2020.
- Monday 9th - 2 course evening meal is included to be held at a local pub within close proximity to Keele Hall.
- Tuesday 10th - Gala Dinner at Keele Hall which is also included (dress code is smart casual).
Bookings will close on 1 November 2020
To find out prices and booking options, please email the Events team.
- Event date
- Event Time
- Dorothy Hodgkin
- School of Medicine
- Contact email
- Contact telephone
- 01782 734601