Regression analysis of dependent current status data with the accelerated failure time model
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Publication:5042202
DOI10.1080/03610918.2020.1797795OpenAlexW3045967379MaRDI QIDQ5042202
Da Xu, Jianguo Sun, Shishun Zhao
Publication date: 18 October 2022
Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/03610918.2020.1797795
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Cites Work
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- Nonparametric regression models for right-censored data using Bernstein polynomials
- A pool-adjacent-violators type algorithm for non-parametric estimation of current status data with dependent censoring
- Nonparametric estimation of current status data with dependent censoring
- Regression analysis of informative current status data with the additive hazards model
- An introduction to copulas.
- On methods of sieves and penalization
- Efficient estimation for the proportional hazards model with interval censoring
- The statistical analysis of interval-censored failure time data.
- Computationally simple accelerated failure time regression for interval censored data
- Semiparametric transformation models for current status data with informative censoring
- A Semiparametric Proportional Odds Regression Model for the Analysis of Current Status Data
- Sieve maximum likelihood regression analysis of dependent current status data
- Additive hazards regression with current status data
- On Profile Likelihood
- Estimates of marginal survival for dependent competing risks based on an assumed copula
- Regression analysis of informative current status data with the semiparametric linear transformation model
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