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An Efficient Procedure for Calculating Sample Size Through Statistical Simulations
http://hdl.handle.net/2241/00151844
http://hdl.handle.net/2241/00151844eafd3303-1967-4f68-a928-2f597247790d
名前 / ファイル | ライセンス | アクション |
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SBR_10-1 (215.1 kB)
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Item type | Journal Article(1) | |||||
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公開日 | 2018-05-30 | |||||
タイトル | ||||||
タイトル | An Efficient Procedure for Calculating Sample Size Through Statistical Simulations | |||||
言語 | ||||||
言語 | eng | |||||
資源タイプ | ||||||
資源 | http://purl.org/coar/resource_type/c_6501 | |||||
タイプ | journal article | |||||
著者 |
Maruo, Kazushi
× Maruo, Kazushi× Tada, Keisuke× Ishii, Ryota× Gosho, Masahiko |
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著者別名 |
丸尾, 和司
× 丸尾, 和司× 五所, 正彦 |
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抄録 | ||||||
内容記述タイプ | Abstract | |||||
内容記述 | While planning clinical trials, when simple formulas are unavailable to calculate sample size, statistical simulations are used instead. However, one has to spend much computation time obtaining adequately precise and accurate simulated sample size estimates, especially when there are many scenarios for the planning and/or the specified statistical method is complicated. In this article, we summarize the theoretical aspect of statistical simulation-based sample size calculation. Then, we propose a new simulation procedure for sample size calculation by fitting the probit model to simulation result data. From the theoretical and simulation-based evaluations, it is suggested that the proposed simulation procedure provide more efficient and accurate sample size estimates than ordinary algorithm-based simulation procedure especially when estimated sample sizes are moderate to large, therefore it would help to dramatically reduce the computational time required to conduct clinical trial simulations. | |||||
書誌情報 |
Statistics in Biopharmaceutical Research 巻 10, 号 1, p. 1-8, 発行日 2018-03 |
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ISSN | ||||||
収録物識別子タイプ | ISSN | |||||
収録物識別子 | 1946-6315 | |||||
DOI | ||||||
識別子タイプ | DOI | |||||
関連識別子 | 10.1080/19466315.2017.1349689 | |||||
権利 | ||||||
権利情報 | This is an Accepted Manuscript of an article published by Taylor & Francis Group in Statistics in Biopharmaceutical Research on 10/07/2017, available online: http://www.tandfonline.com/10.1080/19466315.2017.1349689 | |||||
著者版フラグ | ||||||
値 | author | |||||
出版者 | ||||||
出版者 | AMERICAN STATISTICAL ASSOCIATION's publishing partner Taylor & Francis |