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Statistically testable parameter dru...

Fidler, Matthew Larry.

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Statistically testable parameter drug interaction modeling.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Statistically testable parameter drug interaction modeling./
作者:	Fidler, Matthew Larry.
面頁冊數:	235 p.
附註:	Source: Dissertation Abstracts International, Volume: 66-11, Section: B, page: 5922.
Contained By:	Dissertation Abstracts International66-11B.
標題:	Health Sciences, Pharmacy. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3196618
ISBN:	9780542425936

Statistically testable parameter drug interaction modeling.
Fidler, Matthew Larry.

Statistically testable parameter drug interaction modeling. - 235 p.

Source: Dissertation Abstracts International, Volume: 66-11, Section: B, page: 5922.

Thesis (Ph.D.)--The University of Utah, 2006.

The purpose of this research is to (1) produce a model allowing statistical tests of interaction behavior, (2) assess the model's difference from classical interactions, (3) compare to previous models, (4) find an experimental design to determine the drug ratio of most interaction, and (5) apply the model to a dataset that samples a scope of data where 50% of one drug is not achieved.

ISBN: 9780542425936Subjects--Topical Terms:

1017737
Health Sciences, Pharmacy.

Statistically testable parameter drug interaction modeling.
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245 1 0 $a Statistically testable parameter drug interaction modeling.
300 $a 235 p.
500 $a Source: Dissertation Abstracts International, Volume: 66-11, Section: B, page: 5922.
500 $a Adviser: Steven E. Keen.
502 $a Thesis (Ph.D.)--The University of Utah, 2006.
520 $a The purpose of this research is to (1) produce a model allowing statistical tests of interaction behavior, (2) assess the model's difference from classical interactions, (3) compare to previous models, (4) find an experimental design to determine the drug ratio of most interaction, and (5) apply the model to a dataset that samples a scope of data where 50% of one drug is not achieved.
520 $a The proposed model or STP model gives fits similar in its ability to describe data observed to a polynomial model described by Minto. The model introduces statistically testable summary parameters (STP) for interactions, best ratio for maximum interaction, change in Hill slope, and change in maximum effect. The differences in classification between STP interactions and traditional interactions are small. The STP model can approximate Finney, Single Hill Constant and Minto models.
520 $a The drug ratio giving the most interaction can be estimated by administering set ratios of drugs to at least 10 patients. Without sampling data including the 50% effect of one drug, interaction statements are difficult to make with the STP model alone. Still, the STP model adequately predicts the interaction surfaces.
590 $a School code: 0240.
650 4 $a Health Sciences, Pharmacy. $3 1017737
650 4 $a Statistics. $3 517247
650 4 $a Biology, Biostatistics. $3 1018416
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710 2 0 $a The University of Utah. $3 1017410
773 0 $t Dissertation Abstracts International $g 66-11B.
790 1 0 $a Keen, Steven E., $e advisor
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791 $a Ph.D.
792 $a 2006
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