Using Baseline Data as a Covariate: Can we do better than ANCOVA?
*G. Frank Liu, Merck
In a typical randomized clinical trial, the response of interest is measured pre-treatment (i.e., at baseline, t = 0), and at one or more post-treatment time points (t = 1, …, T). At the end of the trial, it is common practice to report: (i) a point estimate and 95% confidence interval for the mean change from baseline at time T for each treatment group, and (ii) a p-value and 95% confidence interval for the between-group difference in the mean change from baseline. The manner in which the baseline responses are used in the analysis influences both the accuracy and the efficiency of items (i) and (ii). We will contrast the popular ANCOVA approach in which the baseline response is used as a covariate with a longitudinal data analysis (LDA) model proposed by Liang and Zeger (2000), highlighting advantages of the LDA approach over ANCOVA.
April 30 - May 22, 2013
Invited Abstract Submission Open
June 4, 2013
Online Registration Opens
August 9 - August 23, 2013
Invited Abstract Editing
August 23, 2013
Short Course materials due from Instructors
August 26, 2013
September 9, 2013
Cancellation Deadline and Registration Closes @ 11:59 pm EDT
September 16 - September 18, 2013
Marriott Wardman Park, Washington, DC