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020 ▼a 9780438127111
035 ▼a (MiAaPQ)AAI10903105
035 ▼a (MiAaPQ)umichrackham:001243
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0820 ▼a 574
1001 ▼a Chen, Yu-Pu.
24510 ▼a Semiparametric Latent Variable Models for Chronic Diseases with Responses of Multiple Types and Scales.
260 ▼a [S.l.] : ▼b University of Michigan., ▼c 2018
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2018
300 ▼a 199 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
500 ▼a Adviser: Alexander Tsodikov.
5021 ▼a Thesis (Ph.D.)--University of Michigan, 2018.
520 ▼a In chronic diseases, research often centers on discovering a latent trait trajectory that manifests itself through multiple response variables on different measurement scales. In longitudinal studies, it is common to collect multivariate respons
520 ▼a In Chapter II, we study survival models of cancer where a latent trait is responsible for the cure process. Traditional cure models assume that the cure status is determined at the beginning of the follow up. However, patients often receive trea
520 ▼a Chapter III addresses the challenge of latent trait measurement through multiple outcomes of different scales, which are often collected when the construct of interest cannot be measured directly. We proposed a shared latent variable model where
520 ▼a Chapter IV extends the method of Chapter III to allow for longitudinal responses of mixed types. We proposed a joint modeling approach for nonparametrically transformed multivariate longitudinal responses of mixed scales. Multivariate longitudin
590 ▼a School code: 0127.
650 4 ▼a Biostatistics.
690 ▼a 0308
71020 ▼a University of Michigan. ▼b Biostatistics.
7730 ▼t Dissertation Abstracts International ▼g 79-12B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0127
791 ▼a Ph.D.
792 ▼a 2018
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T15000599 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자