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Relevant bibliographies by topics / Censored failure time outcome

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Dissertations / Theses

Academic literature on the topic 'Censored failure time outcome'

Author: Grafiati

Published: 9 March 2023

Last updated: 10 March 2023

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Dissertations / Theses on the topic "Censored failure time outcome"

1

ROTA, MATTEO. "Cut-pont finding methods for continuous biomarkers." Doctoral thesis, Università degli Studi di Milano-Bicocca, 2013. http://hdl.handle.net/10281/40114.

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My PhD dissertation deals with statistical methods for cut-point finding for continuous biomarkers. Categorization is often needed for clinical decision making when dealing with diagnostic (or prognostic) biomarkers and a dichotomous or censored failure time outcome. This allows the definition of two or more prognostic risk groups, or also patient’s stratifications for inclusion in randomized clinical trials (RCTs). We investigate the following cut-point finding methods: minimum P-value, Youden index, concordance probability and point closest to-(0,1) corner in the ROC plane. We compare them

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2

Gorelick, Jeremy Sun Jianguo. "Nonparametric analysis of interval-censored failure time data." Diss., Columbia, Mo. : University of Missouri--Columbia, 2009. http://hdl.handle.net/10355/7009.

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Title from PDF of title page (University of Missouri--Columbia, viewed on Feb 26, 2010). The entire thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file; a non-technical public abstract appears in the public.pdf file. Dissertation advisor: Dr. (Tony) Jianguo Sun. Includes bibliographical references.

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3

Wang, Lianming. "Statistical analysis of multivariate interval-censored failure time data." Diss., Columbia, Mo. : University of Missouri-Columbia, 2006. http://hdl.handle.net/10355/4375.

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Thesis (Ph.D.)--University of Missouri-Columbia, 2006.<br>The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (May 2, 2007) Vita. Includes bibliographical references.

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4

Cai, Jianwen. "Generalized estimating equations for censored multivariate failure time data /." Thesis, Connect to this title online; UW restricted, 1992. http://hdl.handle.net/1773/9581.

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5

Chen, Man-Hua. "Statistical analysis of multivariate interval-censored failure time data." Diss., Columbia, Mo. : University of Missouri-Columbia, 2007. http://hdl.handle.net/10355/4776.

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Thesis (Ph.D.)--University of Missouri-Columbia, 2007.<br>The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on March 6, 2009) Includes bibliographical references.

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6

Zhao, Qiang. "Nonparametric treatment comparisons for interval-censored failure time data /." free to MU campus, to others for purchase, 2004. http://wwwlib.umi.com/cr/mo/fullcit?p3144474.

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7

Zhu, Chao. "Nonparametric and semiparametric methods for interval-censored failure time data." Diss., Columbia, Mo. : University of Missouri-Columbia, 2006. http://hdl.handle.net/10355/4415.

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Thesis (Ph.D.)--University of Missouri-Columbia, 2006.<br>The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (May 2, 2007) Vita. Includes bibliographical references.

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8

Wong, Kin-yau, and 黃堅祐. "Analysis of interval-censored failure time data with long-term survivors." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2012. http://hub.hku.hk/bib/B48199473.

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Failure time data analysis, or survival analysis, is involved in various research fields, such as medicine and public health. One basic assumption in standard survival analysis is that every individual in the study population will eventually experience the event of interest. However, this assumption is usually violated in practice, for example when the variable of interest is the time to relapse of a curable disease resulting in the existence of long-term survivors. Also, presence of unobservable risk factors in the group of susceptible individuals may introduce heterogeneity to the po

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9

Bouadoumou, Maxime K. "Jackknife Empirical Likelihood for the Accelerated Failure Time Model with Censored Data." Digital Archive @ GSU, 2011. http://digitalarchive.gsu.edu/math_theses/112.

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Kendall and Gehan estimating functions are used to estimate the regression parameter in accelerated failure time (AFT) model with censored observations. The accelerated failure time model is the preferred survival analysis method because it maintains a consistent association between the covariate and the survival time. The jackknife empirical likelihood method is used because it overcomes computation difficulty by circumventing the construction of the nonlinear constraint. Jackknife empirical likelihood turns the statistic of interest into a sample mean based on jackknife pseudo-values. U-stat

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10

Goodall, R. L. "Analysis of interval-censored failure time data with application to studies of HIV infection." Thesis, University College London (University of London), 2007. http://discovery.ucl.ac.uk/1446247/.

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In clinical trials and cohort studies the event of interest is often not observable, and is known only to have occurred between the visit when the event was first observed and the previous visit such data are called interval-censored. This thesis develops three pieces of research that build upon published methods for interval-censored data. Novel methods are developed which can be applied via self-written macros in the standard packages, with the aim of increasing the use of appropriate methods in applied medical research. The non-parametric maximum likelihood estimator 1,2 (NPMLE) is the most

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