A general semiparametric maximum likelihood method for Cox regression models with nonmonotone missing at random covariates

Yang Zhao

doi:10.1007/s00180-025-01661-y

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A general semiparametric maximum likelihood method for Cox regression models with nonmonotone missing at random covariates

Yang Zhao

Year: 2025 Journal: Computational Statistics Vol: 40 (9)Pages: 5417-5432 Publisher: Springer Science+Business Media

DOI: 10.1007/s00180-025-01661-y

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Keywords:

Covariate Semiparametric regression Semiparametric model Proportional hazards model Mathematics Econometrics Statistics Regression analysis Regression Computer science Nonparametric statistics

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Statistical Methods and Inference

Physical Sciences → Mathematics → Statistics and Probability

Statistical Methods and Bayesian Inference

Physical Sciences → Mathematics → Statistics and Probability

Bayesian Methods and Mixture Models

Physical Sciences → Computer Science → Artificial Intelligence

A general semiparametric maximum likelihood method for Cox regression models with nonmonotone missing at random covariates

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