| Comparison of Statistical Models Adjusting for Baseline in the Analysis of Parallel-Group Thorough QT/QTc Studies. | |
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MedLine Citation:
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PMID: 22416834 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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The ICH E14 guidance recommends the use of a time-matched baseline, while others recommend alternative baseline definitions including a day-averaged baseline. In this article we consider six models adjusting for baselines. We derive the explicit covariances and compare their power under various conditions. Simulation results are provided. We conclude that type I error rates are controlled. However, one model outperforms the others on statistical power under certain conditions. In general, the analysis of covariance (ANCOVA) model using a day-averaged baseline is preferred. If the time-matched baseline has to be used as per requests from regulatory agencies, the analysis by time point using ANCOVA model should be recommended. |
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Authors:
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Guowen Gordon Sun; Hui Quan; Robert Kringle; Zhaoling Meng |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: Journal of biopharmaceutical statistics Volume: 22 ISSN: 1520-5711 ISO Abbreviation: J Biopharm Stat Publication Date: 2012 May |
Date Detail:
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Created Date: 2012-03-15 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9200436 Medline TA: J Biopharm Stat Country: England |
Other Details:
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Languages: eng Pagination: 438-62 Citation Subset: IM |
Affiliation:
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a Biostatistics and Programming , Celgene Corporation, Summit , New Jersey , USA. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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