Regression analysis of current status data in the presence of dependent censoring with applications to tumorigenicity experiments
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Publication:1658419
DOI10.1016/J.CSDA.2016.12.011zbMath1466.62144OpenAlexW2577314712MaRDI QIDQ1658419
Tao Hu, Jianguo Sun, Shuwei Li, Peijie Wang
Publication date: 14 August 2018
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2016.12.011
Related Items (16)
Nonparametric tests for stratified additive hazards model based on current status data ⋮ An additive hazards cure model with informative interval censoring ⋮ A new approach to estimation of the proportional hazards model based on interval-censored data with missing covariates ⋮ Sharp minimax distribution estimation for current status censoring with or without missing ⋮ New methods for the additive hazards model with the informatively interval‐censored failure time data ⋮ A new approach for regression analysis of multivariate current status data with informative censoring ⋮ Regression analysis of misclassified current status data with informative observation times ⋮ Generalized Odds Rate Frailty Models for Current Status Data with Informative Censoring ⋮ Estimation of linear transformation cure models with informatively interval-censored failure time data ⋮ Combined estimating equation approaches for the additive hazards model with left-truncated and interval-censored data ⋮ Survival function estimation of current status data with dependent censoring ⋮ Estimation of the additive hazards model with case \(K\) interval-censored failure time data in the presence of informative censoring ⋮ Regression analysis of doubly censored data with a cured subgroup under a class of promotion time cure models ⋮ Semiparametric regression analysis of multivariate doubly censored data ⋮ A vine copula approach for regression analysis of bivariate current status data with informative censoring ⋮ Enterprise inefficient investment behavior analysis based on regression analysis
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