| dc.contributor.author | Carter, Jessica Anne | |
| dc.description.abstract | Researchers studying dose-response relationships must allocate limited resources to design points in order to maximize the information gained from the study. D-optimal design is a well-described design that works efficiently to study model parameters. In order to find the D-optimal design, the model that describes the dose-response relationship has to be known. In cases where dose-response relationships show a downturn at high doses, scientists sometimes ignore the downturn to study only the increasing part of the response curve. Here we have two model choices; one describes the overall dose-response relationship, and the other describes only the increasing part of the response curve. The D-optimal designs for these two models will be different and the D-optimal design for one model may not work efficiently for the other model. This research studies robust D-optimal design, a design that works efficiently for both models. | en_US |
| dc.publisher | North Dakota State University | en_US |
| dc.rights | NDSU Policy 190.6.2 | |
| dc.title | Robust D-Optimal Design for Response Functions with a Downturn | en_US |
| dc.type | Master's paper | en_US |
| dc.date.accessioned | 2013-06-26T17:20:32Z | |
| dc.date.available | 2013-06-26T17:20:32Z | |
| dc.date.issued | 2013 | |
| dc.identifier.uri | http://hdl.handle.net/10365/23031 | |
| dc.subject.lcsh | Optimal designs (Statistics) | en_US |
| dc.subject.lcsh | Experimental design. | en_US |
| dc.subject.lcsh | Parameter estimation. | en_US |
| dc.subject.lcsh | Drugs -- Dose-response relationship. | en_US |
| dc.rights.uri | https://www.ndsu.edu/fileadmin/policy/190.pdf | |
| ndsu.degree | Master of Science (MS) | en_US |
| ndsu.college | Science and Mathematics | en_US |
| ndsu.department | Statistics | en_US |
| ndsu.program | Statistics | en_US |
| ndsu.advisor | Hyun, Seung Won | |
