Literature DB >> 17899375

Efficient estimation for the proportional hazards model with bivariate current status data.

Lianming Wang1, Jianguo Sun, Xingwei Tong.   

Abstract

We consider efficient estimation of regression and association parameters jointly for bivariate current status data with the marginal proportional hazards model. Current status data occur in many fields including demographical studies and tumorigenicity experiments and several approaches have been proposed for regression analysis of univariate current status data. We discuss bivariate current status data and propose an efficient score estimation approach for the problem. In the approach, the copula model is used for joint survival function with the survival times assumed to follow the proportional hazards model marginally. Simulation studies are performed to evaluate the proposed estimates and suggest that the approach works well in practical situations. A real life data application is provided for illustration.

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Year:  2008        PMID: 17899375      PMCID: PMC4538960          DOI: 10.1007/s10985-007-9058-9

Source DB:  PubMed          Journal:  Lifetime Data Anal        ISSN: 1380-7870            Impact factor:   1.588


  4 in total

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Review 1.  Interval censoring.

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3.  Maximum likelihood estimation for semiparametric regression models with multivariate interval-censored data.

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Journal:  Biometrika       Date:  2017-07-12       Impact factor: 2.445

  3 in total

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