Keywords: Non-inferiority Test, Bootstrap, Misclassification, Partially Validated Data. / Moreover, misclassification is frequently encountered in collecting ordinal categorical data. We also consider the non-inferiority test based on the data with misclassification. We have explored two different approaches. The first approach can be applied when misclassification probabilities are known or can be calibrated. The second approach deals with the case when we have partially validated data that provide the information on misclassification. The proposed approaches have wide applications that are not confined to tests in medical research. We design a substantive study to illustrate the practicality and applicability of the proposed approaches. / When a new treatment comes out, it is likely to find benefits of the new one, such as fewer side effects, greater convenience of employment, or lower cost in terms of money and time. Therefore, the more appropriate research question is whether the new one is non-inferior or equivalent to, but not necessarily superior to the reference treatment. Consequently, the non-inferiority test or equivalence test is widely used in medical research, which is oriented towards showing that the difference of effect between the two treatments probably lies in a tolerance interval with the pre-defined lower or upper bounds. In this thesis, we consider non-inferiority tests when the data are ordinal categorical. In particular, we are interested in correlated data. We will develop non-inferiority testing procedures for data that are obtained by the paired design and three-armed design. We take advantage of a latent normal distribution approach to model ordinal categorical data. / Han, Yuanyuan. / Adviser: Poon Wai-Yin. / Source: Dissertation Abstracts International, Volume: 73-06, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2011. / Includes bibliographical references (leaves 114-117). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. Ann Arbor, MI : ProQuest Information and Learning Company, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.
| Identifer | oai:union.ndltd.org:cuhk.edu.hk/oai:cuhk-dr:cuhk_344855 |
| Date | January 2011 |
| Contributors | Han, Yuanyuan., Chinese University of Hong Kong Graduate School. Division of Statistics. |
| Source Sets | The Chinese University of Hong Kong |
| Language | English, Chinese |
| Detected Language | English |
| Type | Text, theses |
| Format | electronic resource, microform, microfiche, 1 online resource (xv, 117 leaves : ill.) |
| Rights | Use of this resource is governed by the terms and conditions of the Creative Commons “Attribution-NonCommercial-NoDerivatives 4.0 International” License (http://creativecommons.org/licenses/by-nc-nd/4.0/) |
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