ArticleThe international journal of biostatistics2014
Semiparametric odds rate model for modeling short-term and long-term effects with application to a breast cancer genetic study.
Article in The international journal of biostatistics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Semiparametric frailty models for zero-inflated event count data in the presence of informative dropout.Biometrics · 2019Article
- Quantifying time-varying cause-specific hazard and subdistribution hazard ratios with competing risks data.Clinical trials (London, England) · 2019Article
- A class of semiparametric cure models with current status data.Lifetime data analysis · 2019Article
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Authors and funding
2 authors.
Funding
Abstract
The proportional odds model is commonly used in the analysis of failure time data. The assumption of constant odds ratios over time in the proportional odds model, however, can be violated in some applications. Motivated by a genetic study with breast cancer patients, we propose a novel semiparametric odds rate model for the analysis of right-censored survival data. The proposed model incorporates the short-term and long-term covariate effects on the failure time data and includes the proportional odds model as a nested model. We develop efficient likelihood-based inference procedures and establish the large sample properties of the proposed nonparametric maximum likelihood estimators. Simulation studies demonstrate that the proposed methods perform well in practical settings. An application to the motivating example is provided.
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