Corpus ID: 237503164

Competing Risks Regression for Clustered Data via the Marginal Additive Subdistribution Hazard Model

@inproceedings{Chen2021CompetingRR,
  title={Competing Risks Regression for Clustered Data via the Marginal Additive Subdistribution Hazard Model},
  author={Xinyuan Chen and Denise Esserman and Fan Li},
  year={2021}
}
A population-averaged additive subdistribution hazard model is proposed to assess the marginal effects of covariates on the cumulative incidence function to analyze correlated failure time data subject to competing risks. This approach extends the population-averaged additive hazard model by accommodating potentially dependent censoring due to competing events other than the event of interest. Assuming an independent working correlation structure, an estimating equations approach is considered… Expand

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