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Multivariate optimizing up-and-down ...

Al-Shara, Nawar Marwan.

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Multivariate optimizing up-and-down design.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Multivariate optimizing up-and-down design./
作者:	Al-Shara, Nawar Marwan.
面頁冊數:	95 p.
附註:	Source: Dissertation Abstracts International, Volume: 64-04, Section: B, page: 1787.
Contained By:	Dissertation Abstracts International64-04B.
標題:	Statistics. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3087065

Multivariate optimizing up-and-down design.
Al-Shara, Nawar Marwan.

Multivariate optimizing up-and-down design. - 95 p.

Source: Dissertation Abstracts International, Volume: 64-04, Section: B, page: 1787.

Thesis (Ph.D.)--The American University, 2003.

A Bivariate Optimizing Up-and-Down design for selecting the drug combination with maximum success probability is presented. We assume success is a unimodal function of dose, i.e., too little dose or too much dose both lead to failure. This design is motivated by a stochastic approximation procedure that was developed to work with continuous response and dependent variables. The stochastic approximation procedure is modified to work more efficiently with binary random variables and a finite number of treatment combinations. The procedure is shown to cluster treatments around the treatment that has maximum success probability. We use the mode as an estimator of the best dose and we show the marginal performance of the empirical modes. We show methods of identifying the best dose combination.Subjects--Topical Terms:

517247
Statistics.

Multivariate optimizing up-and-down design.
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245 1 0 $a Multivariate optimizing up-and-down design.
300 $a 95 p.
500 $a Source: Dissertation Abstracts International, Volume: 64-04, Section: B, page: 1787.
500 $a Chair: Nancy Flournoy.
502 $a Thesis (Ph.D.)--The American University, 2003.
520 $a A Bivariate Optimizing Up-and-Down design for selecting the drug combination with maximum success probability is presented. We assume success is a unimodal function of dose, i.e., too little dose or too much dose both lead to failure. This design is motivated by a stochastic approximation procedure that was developed to work with continuous response and dependent variables. The stochastic approximation procedure is modified to work more efficiently with binary random variables and a finite number of treatment combinations. The procedure is shown to cluster treatments around the treatment that has maximum success probability. We use the mode as an estimator of the best dose and we show the marginal performance of the empirical modes. We show methods of identifying the best dose combination.
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650 4 $a Statistics. $3 517247
650 4 $a Health Sciences, Pharmacy. $3 1017737
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710 2 0 $a The American University. $3 1017567
773 0 $t Dissertation Abstracts International $g 64-04B.
790 1 0 $a Flournoy, Nancy, $e advisor
790 $a 0008
791 $a Ph.D.
792 $a 2003
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3087065