Deep historical borrowing framework to prospectively and simultaneously synthesize control information in confirmatory clinical trials with multiple endpoints.

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Title: Deep historical borrowing framework to prospectively and simultaneously synthesize control information in confirmatory clinical trials with multiple endpoints.
Authors: Zhan, Tianyu1 (AUTHOR) tianyu.zhan.stats@gmail.com, Zhou, Yiwang2 (AUTHOR), Geng, Ziqian1 (AUTHOR), Gu, Yihua1 (AUTHOR), Kang, Jian3 (AUTHOR), Wang, Li1 (AUTHOR), Huang, Xiaohong1 (AUTHOR), Slate, Elizabeth H.4 (AUTHOR)
Source: Journal of Biopharmaceutical Statistics. 2022, Vol. 32 Issue 1, p90-106. 17p. 2 Diagrams, 6 Charts, 4 Graphs.
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  Data: Deep historical borrowing framework to prospectively and simultaneously synthesize control information in confirmatory clinical trials with multiple endpoints.
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Biopharmaceutical+Statistics%22">Journal of Biopharmaceutical Statistics</searchLink>. 2022, Vol. 32 Issue 1, p90-106. 17p. 2 Diagrams, 6 Charts, 4 Graphs.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=157108292
RecordInfo BibRecord:
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      – Type: doi
        Value: 10.1080/10543406.2021.1975128
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      – Code: eng
        Text: English
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        PageCount: 17
        StartPage: 90
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      – TitleFull: Deep historical borrowing framework to prospectively and simultaneously synthesize control information in confirmatory clinical trials with multiple endpoints.
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            NameFull: Zhan, Tianyu
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            NameFull: Zhou, Yiwang
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            NameFull: Geng, Ziqian
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            NameFull: Gu, Yihua
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            NameFull: Kang, Jian
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            NameFull: Wang, Li
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            NameFull: Huang, Xiaohong
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            NameFull: Slate, Elizabeth H.
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            – D: 01
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              Text: 2022
              Type: published
              Y: 2022
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            – TitleFull: Journal of Biopharmaceutical Statistics
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