Date: Thursday 14th - Friday 15th October 2021Time: 10:00-12:30 & 14:00-16:30 BST on both daysLocation: OnlinePresenters: Linda Sharples and James Carpenter (LSHTM)Who is this event intended for? This course is suitable for statisticians working on clinical trials, who already have a good understanding of linear and generalised linear models and want to further their knowledge of repeated measures and other clustered data.What is the benefit of attending? By the end of the course attendees will know how to analyse repeated measures of patients through time or other clustered data in randomised clinical trials and associated observational studies. Attendees will develop their knowledge on conditional models for continuous hierarchical and longitudinal data, GEE and discrete models. Pre-recorded lectures will allow trainees to go through course materials when convenient for them and have some time to think over and understand the topics. Practical exercises will allow hands-on experience when working with this type of data and presenters will be available during the course to answer any questions.
Repeated measures of patients through time and other clustered data are common in randomised clinical trials and associated observational studies. Measurements taken from the same patient (or from the same cluster) are likely to be correlated, so that the assumption that all responses will be identically distributed and independent from each other will not hold. Ignoring within-cluster correlation will result in bias in the estimate of the treatment effect standard error and therefore, incorrect confidence intervals and hypothesis tests. In some situations it can also result in bias in the treatment estimate itself. Using a range of worked examples, this course will explain how to analyse repeated measures and other clustered data, with an emphasis on estimating treatment effects using the appropriate covariance structure between measurements. This course is presented through recorded lectures and online practical sessions using SAS code. It is suitable for statisticians working on clinical trials, who already have a good understanding of linear and generalised linear models.Topics covered include:• Conditional models for continuous hierarchical data• Conditional models for continuous longitudinal data• Marginal models (GEE) for continuous longitudinal data• Discrete data
NB: This course has Early-Bird rates available. These are valid for bookings on or before 17:00 BST Wednesday 15th September only.Early-bird Members = £300+VATEarly-bird Non-Members = £425+VAT*Regular Members = £340+VATRegular Non-Members = £465+VAT**Please note: Non-Member rates include membership for the rest of the 2021, and entirety of the 2022 calendar year.
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