A Multiple Imputation Approach to the Analysis of Current Status Data with the Additive Hazards Model

DOI10.1080/03610920802361407zbMath1162.62093OpenAlexW2121143471MaRDI QIDQ3631429

Ling Chen, Jianguo Sun

Publication date: 9 June 2009

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: http://www.informaworld.com/smpp/./content~db=all~content=a909714334

zbMATH Keywords

multiple imputationadditive hazards modelcurrent status datalung tumorstumorigenicity experiment

Mathematics Subject Classification ID

Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Applications of statistics to biology and medical sciences; meta analysis (62P10) Censored data models (62N01) Estimation in survival analysis and censored data (62N02)

Related Items (7)

Regression analysis of current status data with auxiliary covariates and informative observation times ⋮ Regression analysis of case II interval-censored data with auxiliary covariates ⋮ Regression analysis of multivariate current status data with auxiliary covariates under the additive hazards model ⋮ Regression analysis of multivariate current status data under a varying coefficients additive hazards frailty model ⋮ Nonparametric maximum likelihood analysis of clustered current status data with the gamma-frailty Cox model ⋮ Regression Analysis of Current Status Data Under the Additive Hazards Model with Auxiliary Covariates ⋮ Regression analysis of informative current status data with the additive hazards model

Cites Work

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• A Semiparametric Proportional Odds Regression Model for the Analysis of Current Status Data
• Additive hazards regression with current status data
• Semiparametric analysis of the additive risk model
• Efficient estimation in additive hazards regression with current status data
• A Multiple Imputation Approach to Cox Regression with Interval‐Censored Data
• Age-Specific Incidence and Prevalence: A Statistical Perspective

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