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Apply response adaptive randomizatio...

Jiang, Fei.

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Apply response adaptive randomization to group sequential with early stopping.

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Apply response adaptive randomization to group sequential with early stopping./
作者:	Jiang, Fei.
面頁冊數:	63 p.
附註:	Source: Masters Abstracts International, Volume: 48-02, page: 1072.
Contained By:	Masters Abstracts International48-02.
標題:	Statistics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1470102
ISBN:	9781109473346

Apply response adaptive randomization to group sequential with early stopping.
Jiang, Fei.

Apply response adaptive randomization to group sequential with early stopping. - 63 p.

Source: Masters Abstracts International, Volume: 48-02, page: 1072.

Thesis (M.S.)--The University of Texas School of Public Health, 2009.

Group sequential methods and response adaptive randomization (RAR) procedures have been applied in clinical trials due to economical and ethical considerations. Group sequential methods are able to reduce the average sample size by inducing early stopping, but patients are equally allocated with half of chance to inferior arm. RAR procedures incline to allocate more patients to better arm; however it requires more sample size to obtain a certain power. This study intended to combine these two procedures. We applied the Bayesian decision theory approach to define our group sequential stopping rules and evaluated the operating characteristics under RAR setting. The results showed that Bayesian decision theory method was able to preserve the type I error rate as well as achieve a favorable power; further by comparing with the error spending function method, we concluded that Bayesian decision theory approach was more effective on reducing average sample size.

ISBN: 9781109473346Subjects--Topical Terms:

517247
Statistics.

Apply response adaptive randomization to group sequential with early stopping.
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500 $a Source: Masters Abstracts International, Volume: 48-02, page: 1072.
500 $a Advisers: J. Jack Lee; Dejian Lai.
502 $a Thesis (M.S.)--The University of Texas School of Public Health, 2009.
520 $a Group sequential methods and response adaptive randomization (RAR) procedures have been applied in clinical trials due to economical and ethical considerations. Group sequential methods are able to reduce the average sample size by inducing early stopping, but patients are equally allocated with half of chance to inferior arm. RAR procedures incline to allocate more patients to better arm; however it requires more sample size to obtain a certain power. This study intended to combine these two procedures. We applied the Bayesian decision theory approach to define our group sequential stopping rules and evaluated the operating characteristics under RAR setting. The results showed that Bayesian decision theory method was able to preserve the type I error rate as well as achieve a favorable power; further by comparing with the error spending function method, we concluded that Bayesian decision theory approach was more effective on reducing average sample size.
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710 2 $a The University of Texas School of Public Health. $b Biostatistics. $3 1018615
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790 1 0 $a Lee, J. Jack, $e advisor
790 1 0 $a Lai, Dejian, $e advisor
790 1 0 $a Kapadia, Asha S $e committee member
790 1 0 $a Mueller, Peter $e committee member
790 1 0 $a Xiong, Momiao $e committee member
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