Copula Based Cox Proportional Hazards Models for Dependent Censoring
Overview
Copula based Cox proportional hazards models for survival data subject to dependent censoring. This approach does not assume that the parameter defining the copula is known. The dependency parameter is estimated with other finite model parameters by maximizing a Pseudo likelihood function. The cumulative hazard function is estimated via estimating equations derived based on martingale ideas. Available copula functions include Frank, Gumbel and Normal copulas. Only Weibull and lognormal models are allowed for the censoring model, even though any parametric model that satisfies certain identifiability conditions could be used. Implemented methods are described in the article "Copula based Cox proportional hazards models for dependent censoring" by Deresa and Van Keilegom (2024) doi:10.1080/01621459.2022.2161387.
- Add the number of cores as argument and increase the default number of bootstrap samples
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- OK14 OK2026-03-10
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Dependencies
Installing SemiPar.depCens adds 13 packages (7 with compiled code, 7.5 MB of source tarballs). Heaviest: copula 3.5 MB, colorspace 2.0 MB, mvtnorm 1.0 MB.
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Package metadata
- First published
- 2024-02-29
- Total releases
- 3 / 2 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 6.4 KB / 1 file
- Download size
- 25 KB
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