| LDR | | 02580nmm uu200421 4500 |
| 001 | | 000000333922 |
| 005 | | 20240805174806 |
| 008 | | 181129s2018 |||||||||||||||||c||eng d |
| 020 | |
▼a 9780438125452 |
| 035 | |
▼a (MiAaPQ)AAI10902938 |
| 035 | |
▼a (MiAaPQ)umichrackham:001208 |
| 040 | |
▼a MiAaPQ
▼c MiAaPQ
▼d 248032 |
| 082 | 0 |
▼a 574 |
| 100 | 1 |
▼a Dharmarajan, Sai Hurrish. |
| 245 | 10 |
▼a Methods for Clustered Competing Risks Data and Causal Inference using Instrumental Variables for Censored Time-to-event Data. |
| 260 | |
▼a [S.l.] :
▼b University of Michigan.,
▼c 2018 |
| 260 | 1 |
▼a Ann Arbor :
▼b ProQuest Dissertations & Theses,
▼c 2018 |
| 300 | |
▼a 127 p. |
| 500 | |
▼a Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B. |
| 500 | |
▼a Adviser: Douglas E. Schaubel. |
| 502 | 1 |
▼a Thesis (Ph.D.)--University of Michigan, 2018. |
| 520 | |
▼a In this dissertation, we propose new methods for analysis of clustered competing risks data (Chapters 1 and 2) and for instrumental variable (IV) analysis of univariate censored time-to-event data and competing risks data (Chapters 3 and 4). |
| 520 | |
▼a In Chapter 1, we propose estimating center effects through cause-specific proportional hazards frailty models that allow correlation among a center's cause-specific effects. To evaluate center performance, we propose a directly standardized exce |
| 520 | |
▼a In Chapter 2, we propose to model the effects of cluster and individual-level covariates directly on the cumulative incidence functions of each risk through a semiparametric mixture component model with cluster-specific random effects. Our model |
| 520 | |
▼a In Chapter 3, we turn our focus to causal inference in the censored time-to-event setting in the presence of unmeasured confounders. We develop weighted IV estimators of the complier average causal effect on the restricted mean survival time. Ou |
| 520 | |
▼a In Chapter 4, we develop IV analysis methods for competing risks data. Our method permits simultaneous inference of exposure effects on the absolute risk of all competing events and accommodates exposure dependent censoring. We apply the methods |
| 590 | |
▼a School code: 0127. |
| 650 | 4 |
▼a Biostatistics. |
| 690 | |
▼a 0308 |
| 710 | 20 |
▼a University of Michigan.
▼b Biostatistics. |
| 773 | 0 |
▼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 |
| 856 | 40 |
▼u http://www.riss.kr/pdu/ddodLink.do?id=T15000448
▼n KERIS |
| 980 | |
▼a 201812
▼f 2019 |
| 990 | |
▼a 관리자 |