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Activity Number: 430
Type: Contributed
Date/Time: Tuesday, August 2, 2016 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract #319536 View Presentation
Title: Detecting Treatment Differences in Group Sequential Longitudinal Studies with Covariate Adjustment
Author(s): Neal Jeffries* and James Troendle and Nancy L. Geller
Companies: National Heart, Lung, and Blood Institute and National Institutes of Health and National Heart, Lung, and Blood Institute
Keywords: Longitudinal analysis ; Group sequential design ; Clinical trial design ; Generalized estimation equations

In longitudinal studies comparing two treatments over a series of common follow-up measurements there may be interest in determining if there is a treatment difference at any follow-up period when there may be a non-monotone treatment effect over time. To evaluate this question Jeffries and Geller (2015) examined a number of clinical trial designs that allowed adaptive choice of the follow-up time exhibiting the greatest evidence of treatment difference in a group sequential testing setting with Gaussian data. The methods were applicable when a few measurements were taken at prespecified follow-up periods, such as in in ancillary studies. Here we test the composite null hypothesis of no difference at any follow-up time versus the alternative that there is a difference for at least one follow-up time. Results of Jeffries and Geller (2015) are extended by considering a broader range of modeled data and the inclusion of covariates using generalized estimating equations. Closed testing procedures are developed to determine a set of follow-up times that exhibit a treatment difference.

Authors who are presenting talks have a * after their name.

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