TY - GEN
T1 - Quantiles of residual survival
AU - Cox, Christopher
AU - Schneider, Michael F.
AU - Muñoz, Alvaro
N1 - Funding Information:
Data in this manuscript were collected by the Multicenter AIDS Cohort Study (MACS) with centers (Principal Investigators) at The Johns Hopkins Bloomberg School of Public Health (Joseph B. Margolick, Lisa P. Jacobson), Howard Brown Health Center, Feinberg School of Medicine, Northwestern University, and Cook County Bureau of Health Services (John P. Phair), University of California, Los Angeles (Roger Detels), and University of Pittsburgh (Charles Rinaldo). The MACS is funded by the National Institute of Allergy and Infectious Diseases, with supplemental funding from the National Cancer Institute. U01-AI-35042, UL1-RR025005, U01-AI-35043, U01-AI-35039, U01-AI-35040, U01-AI-35041.
Funding Information:
Data in this manuscript were collected by the Women’s Interagency HIV Study (WIHS) Collaborative Study Group with centers (Principal Investigators) at New York City/Bronx Consortium (Kathryn Anastos); Brooklyn, NY (Howard Minkoff); Washington, DC Metropolitan Consortium (Mary Young); The Connie Wofsy Study Consortium of Northern California (Ruth Greenblatt); Los Angeles County/Southern California Consortium (Alexandra Levine); Chicago Consortium (Mardge Cohen); Data Coordinating Center (Stephen Gange). The WIHS is funded by the National Institute of Allergy and Infectious Diseases (U01-AI-35004, U01-AI-31834, U01-AI-34994, U01-AI-34989, U01-AI-34993, and U01-AI-42590) and by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (U01-HD-32632). The study is co-funded by the National Cancer Institute, the National Institute on Drug Abuse, and the National Institute on Deafness and Other Communication Disorders. Funding is also provided by the National Center for Research Resources (UCSF-CTSI Grant Number UL1 RR024131).
Publisher Copyright:
© Springer Science+Business Media New York 2013.
PY - 2013
Y1 - 2013
N2 - In reliability theory, the lifetime remaining in a network of components after an initial run-in period is an important property of the system. Similarly, for medical interventions residual survival characterizes the subsequent experience of patients who survive beyond the beginning of follow-up. Here we show how quantiles of the residual survival distribution can be used to provide such a characterization. We first discuss properties of the residual quantile function and its close relationship to the hazard function.We then consider parametric estimation of the residual quantile function, focusing on the generalized gamma distribution. Finally, we describe an application of quantiles of residual survival to help describe the effects at the population level of the introduction and sustained use of highly active antiretroviral therapy for the treatment of HIV/AIDS.
AB - In reliability theory, the lifetime remaining in a network of components after an initial run-in period is an important property of the system. Similarly, for medical interventions residual survival characterizes the subsequent experience of patients who survive beyond the beginning of follow-up. Here we show how quantiles of the residual survival distribution can be used to provide such a characterization. We first discuss properties of the residual quantile function and its close relationship to the hazard function.We then consider parametric estimation of the residual quantile function, focusing on the generalized gamma distribution. Finally, we describe an application of quantiles of residual survival to help describe the effects at the population level of the introduction and sustained use of highly active antiretroviral therapy for the treatment of HIV/AIDS.
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U2 - 10.1007/978-1-4614-8981-8_6
DO - 10.1007/978-1-4614-8981-8_6
M3 - Conference contribution
AN - SCOPUS:84945963631
SN - 9781461489801
T3 - Lecture Notes in Statistics
SP - 87
EP - 103
BT - Risk Assessment and Evaluation of Predictions
A2 - Gandy, Axel
A2 - Satten, Glen
A2 - Gail, Mitchell
A2 - Pfeiffer, Ruth
A2 - Cai, Tianxi
A2 - Lee, Mei-Ling Ting
PB - Springer Science and Business Media, LLC
T2 - International conference on Risk Assessment and Evaluation of Predictions, 2011
Y2 - 12 October 2011 through 14 October 2011
ER -