Registration will close October 6, 2021 at


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 with 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 module will explain how to analyse repeated measures and other clustered data, with a focus on estimating treatment effects using the appropriate covariance structure between measurements.

This module 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

Tickets

  • Member Early-Bird

    £300.-

    Member Early Bird Price

    Buy Ticket
  • Member

    £340.-

    Member Price

    Buy Ticket
  • Non-Member Early-Bird

    £425.-

    Early Bird Price

    *Includes PSI membership for the remainder of the 2021, and entirety of the 2022 calendar year.

    Buy Ticket
  • Non-Member

    £465.-

    Public Price

    *Includes PSI membership for the remainder of the 2021, and entirety of the 2022 calendar year.

    Buy Ticket

Sponsors and Partners

Community

Discover and connect with other attendees.

SBLLJV
Register & Join the Community