 Detecting treatment differences in group sequential longitudinal studies with covariate adjustmentNeal O. Jeffries, James F. Troendle and Nancy L. Geller Biometrics, 2018, vol. 74, issue 3, 1072-1081 Abstract: 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 are applicable when a few measurements were taken at prespecified follow‐up periods. Here, we test the intersection 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. Testing procedures are developed to determine a set of follow‐up times that exhibit a treatment difference that accounts for multiplicity in follow‐up times and interim analyses. Date: 2018 Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:bla:biomet:v:74:y:2018:i:3:p:1072-1081 Ordering information: This journal article can be ordered from Access Statistics for this article More articles in Biometrics from The International Biometric Society |
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