Semiparametric Sequential Testing for Multiple Change Points in Piecewise Constant Hazard Functions with Long-Term Survivors

DOI10.1080/03610918.2012.742106zbMath1333.62235OpenAlexW2025389693MaRDI QIDQ5418896

Wei Zhang, Lianfen Qian, Yun Xia Li

Publication date: 30 May 2014

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610918.2012.742106

zbMATH Keywords

right censoringchange pointshazard ratelong-term survivor

Mathematics Subject Classification ID

Censored data models (62N01) Sequential statistical analysis (62L10) Estimation in survival analysis and censored data (62N02) Testing in survival analysis and censored data (62N03)

Related Items (8)

Bayesian multiple change-points estimation for hazard with censored survival data from exponential distributions ⋮ Survival model induced by discrete frailty for modeling of lifetime data with long-term survivors and change-point ⋮ Estimation in a change-point hazard regression model with long-term survivors ⋮ Semiparametric method for detecting multiple change points model in financial time series ⋮ Multiple Change-Point Detection in Piecewise Exponential Hazard Regression Models with Long-Term Survivors and Right Censoring ⋮ Semiparametric test for multiple change-points based on empirical likelihood ⋮ Estimation of a change point in the hazard rate of Lindley model under right censoring ⋮ Semiparametric Estimation of a Change-point for Recurrent Events Data

Cites Work

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• Likelihood ratio tests for continuous monotone hazards with an unknown change point
• Asymptotic score-statistic processes and tests for constant hazard against a change-point alternative
• Estimation of a change point in a hazard function based on censored data
• Estimation in a change-point hazard regression model
• Inference for a hazard rate change point
• Likelihood ratio tests for a changepoint with survival data
• Estimation in change-point hazard rate models
• A Simplex Method for Function Minimization
• Strong consistency of the maximum likelihood estimators in the change-point hazard bate model

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