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Multivariate optimizing up-and-down ...

Al-Shara, Nawar Marwan.

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Multivariate optimizing up-and-down design.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Multivariate optimizing up-and-down design./
Author:	Al-Shara, Nawar Marwan.
Description:	95 p.
Notes:	Source: Dissertation Abstracts International, Volume: 64-04, Section: B, page: 1787.
Contained By:	Dissertation Abstracts International64-04B.
Subject:	Statistics. -
Online resource:	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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100 1 $a Al-Shara, Nawar Marwan. $3 1952094
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.
590 $a School code: 0008.
650 4 $a Statistics. $3 517247
650 4 $a Health Sciences, Pharmacy. $3 1017737
690 $a 0463
690 $a 0572
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