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Efficient Semiparametric Estimation of Short-term and Long-term Hazard Ratios with Right-Censored Data | | Guoqing Diao
; Donglin Zeng
; Song Yang
; | | Date: |
5 Jun 2012 | | Abstract: | The proportional hazards assumption in the commonly used Cox model for
censored failure time data is often violated in scientific studies. Yang and
Prentice (2005) proposed a novel semiparametric two-sample model that includes
the proportional hazards model and the proportional odds model as sub-models,
and accommodates crossing survival curves. The model leaves the baseline hazard
unspecified and the two model parameters can be interpreted as the short-term
and long-term hazard ratios. Inference procedures were developed based on a
pseudo score approach. Although extension to accommodate covariates was
mentioned, no formal procedures have been provided or proved. Furthermore, the
pseudo score approach may not be asymptotically efficient. We study the
extension of the short-term and long-term hazard ratio model of Yang and
Prentice (2005) to accommodate potentially time-dependent covariates. We
develop efficient likelihood-based estimation and inference procedures. The
nonparametric maximum likelihood estimators are shown to be consistent,
asymptotically normal, and asymptotically efficient. Extensive simulation
studies demonstrate that the proposed methods perform well in practical
settings. The proposed method captured the phenomenon of crossing hazards in a
cancer clinical trial and identified a genetic marker with significant
long-term effect missed by using the proportional hazards model on age-at-onset
of alcoholism in a genetic study. | | Source: | arXiv, 1206.0980 | | Services: | Forum | Review | PDF | Favorites | |
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