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Recursos bibliográficos en papel y digitales -
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» Resultado: 2 registros
| Registro 1 de 2 | |
| Autor: | Hudgens, Michael G. - Maathuis, Marloes H. - Gilbert, Peter B. - |
| Título: | Nonparametric estimation of the joint distribution of a survival time subject to interval censoring and a continuous mark variable |
| Fuente: | Biometrics. v.63, n.2. International Biometric Society |
| Páginas: | pp. 372-380 |
| Año: | jun. 2007 |
| Resumen: | This article considers three nonparametric estimators of the joint distribution function for a survival time and a continuous mark variable when the survival time is interval censored and the mark variable may be missing for interval-censored observations. Finite and large sample properties are described for the nonparametric maximum likelihood estimator (NPMLE) as well as estimators based on midpoint imputation (MIDMLE) and coarsening the mark variable (CMLE). The estimators are compared using data from a simulation study and a recent phase III HIV vaccine efficacy trial where the survival time is the time from enrollment to infection and the mark variable is the genetic distance from the infecting HIV sequence to the HIV sequence in the vaccine. Theoretical and empirical evidence are presented indicating the NPMLE and MIDMLE are inconsistent. Conversely, the CMLE is shown to be consistent in general and thus is preferred. |
| Solicitar por: | HEMEROTECA B + datos de Fuente |
| Registro 2 de 2 | |
| Autor: | Gilbert, Peter B. - Bosch, Ronald J. - Hudgens, Michael G. - |
| Título: | Sensitivity analysis for the assessment of causal vaccine effects on viral load in HIV vaccine trials |
| Fuente: | Biometrics. v.59, n.3. International Biometric Society |
| Páginas: | pp. 531-541 |
| Año: | sep. 2003 |
| Resumen: | Vaccines with limited ability to prevent HIV infection may positively impact the HIV/AIDS pandemic by preventing secondary transmission and disease in vaccine recipients who become infected. To evaluate the impact of vaccination on secondary transmission and disease, efficacy trials assess vaccine effects on HIV viral load and other surrogate endpoints measured after infection. A standard test that compares the distribution of viral load between the infected subgroups of vaccine and placebo recipients does not assess a causal effect of vaccine, because the comparison groups are selected after randomization. To address this problem, we formulate clinically relevant causal estimands using the principal stratification framework developed by Frangakis and Rubin (2002, Biometrics 58, 21-29), and propose a class of logistic selection bias models whose members identify the estimands. Given a selection model in the class, procedures are developed for testing and estimation of the causal effect of vaccination on viral load in the principal stratum of subjects who would be infected regardless of randomization assignment. We show how the procedures can be used for a sensitivity analysis that quantifies how the causal effect of vaccination varies with the presumed magnitude of selection bias. |
| Solicitar por: | HEMEROTECA B + datos de Fuente |
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