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Design and Analysis of Trials for Developing Adaptive Treatment Strategies in Complex Clustered Settings.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Design and Analysis of Trials for Developing Adaptive Treatment Strategies in Complex Clustered Settings./
作者:	Ktsanes, Rachel.
面頁冊數:	1 online resource (377 pages)
附註:	Source: Dissertation Abstracts International, Volume: 79-02(E), Section: B.
Contained By:	Dissertation Abstracts International79-02B(E).
標題:	Statistics. -
電子資源:	click for full text (PQDT)
ISBN:	9780355298109

Design and Analysis of Trials for Developing Adaptive Treatment Strategies in Complex Clustered Settings.
Ktsanes, Rachel.

Design and Analysis of Trials for Developing Adaptive Treatment Strategies in Complex Clustered Settings. - 1 online resource (377 pages)

Source: Dissertation Abstracts International, Volume: 79-02(E), Section: B.

Thesis (Ph.D.)

Includes bibliographical references

In recent years, research has been conducted to develop Sequential, Multiple Assignment, Randomized Trial (SMART) designs. These experimental designs were created to aid in the construction of adaptive treatment strategies for individuals, particularly in medical contexts. Simultaneously, research has been done on developing the use of randomized trials to evaluate static treatments in clustered settings. For example, methodology for evaluating academic interventions in schools has been researched extensively. The benefits individuals experience by following adaptive treatment strategies can be expected to extend to individuals in clustered settings, as well. This work helps bridge these two lines of research by proposing and evaluating experimental designs for developing adaptive treatment strategies in clustered settings.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2018

Mode of access: World Wide Web

ISBN: 9780355298109Subjects--Topical Terms:

556824
Statistics.
Index Terms--Genre/Form:

554714
Electronic books.

Design and Analysis of Trials for Developing Adaptive Treatment Strategies in Complex Clustered Settings.
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500 $a Source: Dissertation Abstracts International, Volume: 79-02(E), Section: B.
500 $a Adviser: Larry V. Hedges.
502 $a Thesis (Ph.D.) $c Northwestern University $d 2017.
504 $a Includes bibliographical references
520 $a In recent years, research has been conducted to develop Sequential, Multiple Assignment, Randomized Trial (SMART) designs. These experimental designs were created to aid in the construction of adaptive treatment strategies for individuals, particularly in medical contexts. Simultaneously, research has been done on developing the use of randomized trials to evaluate static treatments in clustered settings. For example, methodology for evaluating academic interventions in schools has been researched extensively. The benefits individuals experience by following adaptive treatment strategies can be expected to extend to individuals in clustered settings, as well. This work helps bridge these two lines of research by proposing and evaluating experimental designs for developing adaptive treatment strategies in clustered settings.
520 $a This research first proposes experimental designs in which the unit of treatment changes over the course of the trial, and in which individuals within a clustered setting are regrouped mid-trial to receive further treatment based on initial treatment response. Sample size formulae are derived to allow researchers to properly power these trials. Sample sizes for the proposed designs are evaluated in a sensitivity analysis. Next, methods of analyzing data from individual SMARTs are adapted for use with the data that would be obtained from the proposed trial designs. These adapted methods are evaluated through a simulation study.
520 $a Finally, a web application is created to allow easy dissemination of the research presented here. The findings of this research suggest that complex clustered SMART designs can be feasibly implemented, presenting the opportunity to bring improved treatment strategies at lower resource requirements, as compared to existing options, to clustered settings. Furthermore, findings of this research suggest that existing SMART data analysis methods can be successfully adapted to accommodate the clustered data arising from the proposed designs.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2018
538 $a Mode of access: World Wide Web
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710 2 $a Northwestern University. $b Statistics. $3 1183000
773 0 $t Dissertation Abstracts International $g 79-02B(E).
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