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Activity Number: 71 - Longitudinal/Correlated Data
Type: Contributed
Date/Time: Sunday, July 28, 2019 : 4:00 PM to 5:50 PM
Sponsor: Biometrics Section
Abstract #304522 Presentation
Title: Detecting Treatment Differences in Group Sequential Multivariate Longitudinal Studies with Covariate Adjustment
Author(s): Neal Jeffries* and Nancy Geller and James Troendle
Companies: National Heart, Lung, and Blood Institute,-NIH and National Institutes of Health, NHLBI and National Institutes of Health
Keywords: multivariate analysis; longitudinal analysis; group sequential design; generalized estimating equations

Jeffries, Troendle, and Geller (2018) investigated testing for a treatment difference in a randomized clinical trial with a single outcome measured longitudinally over a series of common follow-up times. This testing examined the 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. This previous work is extended here by considering multivariate outcome measurements. Such considerations may arise when there is a desire to test the individual outcomes simultaneously with equal weight. Alternatively, there may be interest in first testing for a treatment difference in a global function of the outcomes (e.g. sum) with subsequent interest in examining the individual outcomes if the function shows a treatment difference. In either case, testing is conducted for each follow-up time and may be performed in a group sequential manner. Procedures are developed to determine follow-up time(s) for which a treatment difference exists and which combinations of outcome measurement and follow-up time show evidence of a difference while controlling for multiplicity in outcomes, follow-up, and interim analyses.

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

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