Comput Math Methods Med - An empirical likelihood method for semiparametric linear regression with right censored data.

Tópicos

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Resumo

This paper develops a new empirical likelihood method for semiparametric linear regression with a completely unknown error distribution and right censored survival data. The method is based on the Buckley-James (1979) estimating equation. It inherits some appealing properties of the complete data empirical likelihood method. For example, it does not require variance estimation which is problematic for the Buckley-James estimator. We also extend our method to incorporate auxiliary information. We compare our method with the synthetic data empirical likelihood of Li and Wang (2003) using simulations. We also illustrate our method using Stanford heart transplantation data.

Resumo Limpo

paper develop new empir likelihood method semiparametr linear regress complet unknown error distribut right censor surviv data method base buckleyjam estim equat inherit appeal properti complet data empir likelihood method exampl requir varianc estim problemat buckleyjam estim also extend method incorpor auxiliari inform compar method synthet data empir likelihood li wang use simul also illustr method use stanford heart transplant data

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