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Inference on Risk Rates Based on Mortality Data Under Censoring and Competing Risks Using Parametric Models
Author(s) -
Kundu D.,
Kannan N.,
Mazumdar M.
Publication year - 1992
Publication title -
biometrical journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.108
H-Index - 63
eISSN - 1521-4036
pISSN - 0323-3847
DOI - 10.1002/bimj.4710340306
Subject(s) - censoring (clinical trials) , weibull distribution , parametric statistics , statistics , mathematics , parametric model , inference , monte carlo method , econometrics , fisher information , statistical inference , confidence interval , exponential distribution , computer science , artificial intelligence
In this paper we consider the competing risks model where the risks may not be independent. We assume both fixed and random censoring. The random censoring mechanism could have either a parametric or a non‐parametric form. The life distributions and the parametric censoring distribution considered are exponential or Weibull. The expressions for the asymptotic confidence intervals for various parameters of interest under different models, using the estimated Fisher information matrix and parametric bootstrap techniques have been derived. Monte Carlo simulation studies for some of these cases have been carried out.