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http://dx.doi.org/10.5351/KJAS.2016.29.7.1231

Estimation methods and interpretation of competing risk regression models  

Kim, Mijeong (Department of Statistics, Ewha Womans University)
Publication Information
The Korean Journal of Applied Statistics / v.29, no.7, 2016 , pp. 1231-1246 More about this Journal
Abstract
Cause-specific hazard model (Prentice et al., 1978) and subdistribution hazard model (Fine and Gray, 1999) are mostly used for the right censored survival data with competing risks. Some other models for survival data with competing risks have been subsequently introduced; however, those models have not been popularly used because the models cannot provide reliable statistical estimation methods or those are overly difficult to compute. We introduce simple and reliable competing risk regression models which have been recently proposed as well as compare their methodologies. We show how to use SAS and R for the data with competing risks. In addition, we analyze survival data with two competing risks using five different models.
Keywords
proportional odds models; competing risks; cumulative incidence function; subdistribution;
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