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| Main Authors: | , , |
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| Format: | Preprint |
| Published: |
2023
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2310.14448 |
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| _version_ | 1866929343674974208 |
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| author | Rava, Denise Bradic, Jelena Xu, Ronghui |
| author_facet | Rava, Denise Bradic, Jelena Xu, Ronghui |
| contents | We consider a general proportional odds model for survival data under binary treatment, where the functional form of the covariates is left unspecified. We derive the efficient score for the conditional survival odds ratio given the covariates using modern semiparametric theory. The efficient score may be useful in the development of doubly robust estimators, although computational challenges remain. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2310_14448 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Semiparametrically Efficient Score for the Survival Odds Ratio Rava, Denise Bradic, Jelena Xu, Ronghui Methodology We consider a general proportional odds model for survival data under binary treatment, where the functional form of the covariates is left unspecified. We derive the efficient score for the conditional survival odds ratio given the covariates using modern semiparametric theory. The efficient score may be useful in the development of doubly robust estimators, although computational challenges remain. |
| title | Semiparametrically Efficient Score for the Survival Odds Ratio |
| topic | Methodology |
| url | https://arxiv.org/abs/2310.14448 |