Nonparametric estimation of quality adjusted lifetime distribution in a simple illness-death model

DOI10.1080/02331888.2012.672421zbMath1440.62355OpenAlexW2162550477MaRDI QIDQ2863087

Anup Dewanji, Alok Goswami, Biswabrata Pradhan

Publication date: 21 November 2013

Published in: Unnamed Author (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02331888.2012.672421

zbMATH Keywords

weak convergenceconsistencyEM algorithmGaussian processKaplan-Meier estimatequality adjusted lifetimeillness-death model

Mathematics Subject Classification ID

Asymptotic properties of nonparametric inference (62G20) Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05) Estimation in survival analysis and censored data (62N02) Reliability and life testing (62N05)

Related Items (2)

Nonparametric estimator for the survival function of quality adjusted lifetime (QAL) in a three-state illness-death model ⋮ Nonparametric estimation of quality adjusted lifetime distribution in a simple illness-death model

Cites Work

• Unnamed Item
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• THE APPROPRIATE REDUCTION OF THE WEIGHTED EMPIRICAL PROCESS
• Nonparametric estimation of the joint distribution of survival time and mark variables
• Nonparametric estimation of the gap time distribution for serial events with censored data
• On estimating the distribution function for quality of life in cancer clinical trials
• A consistent estimator for the distribution of quality adjusted survival time
• Locally Efficient Estimation of the Quality‐Adjusted Lifetime Distribution with Right‐Censored Data and Covariates
• Efficient Estimation of the Distribution of Quality‐Adjusted Survival Time
• Monotonic Estimators for the Survival Function of Quality Adjusted Lifetime
• Semiparametric Estimation in a Three-State Duration-Dependent Markov Model from Interval-Censored Observations with Application to AIDS Data
• Parametric Estimation of Quality Adjusted Lifetime (QAL) Distribution in Simple Illness-Death Model

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