| dc.contributor.author | Lexvold, Andrew Michael | |
| dc.description.abstract | The Optimal designs used in a clinical trial depends on the goals of the study. Common goals are estimating model parameters and choosing between models. D-optimal designs are used when the goal is to estimate the model parameters. This is achieved by maximizing the determinant of the information matrix. When the goal is model discrimination, T-optimal designs are used. The design is optimal when the minimum difference between the models is maximized. Generally, D-optimal designs are not efficient when the goal is model discrimination and T-optimal designs perform poorly when the goal is parameter estimation. However, because D-optimal and T-optimal designs have a common criterion structure, they can be combined into a new design called a DT-optimal design. DT-optimal designs provide a balance between parameter estimation and model discrimination. The efficiency of DT-optimal designs relative to D and T-optimal designs shows that they work for parameter estimation and model discrimination. | en_US |
| dc.publisher | North Dakota State University | en_US |
| dc.rights | NDSU Policy 190.6.2 | |
| dc.title | DT-Optimal Designs for Probit Models in Clinical Trials | en_US |
| dc.type | Thesis | en_US |
| dc.date.accessioned | 2018-03-28T19:08:37Z | |
| dc.date.available | 2018-03-28T19:08:37Z | |
| dc.date.issued | 2015 | en_US |
| dc.identifier.uri | https://hdl.handle.net/10365/27904 | |
| 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 | |
