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Linear transformation models for censored data under truncation

Dai, H and Wang, H and Restaino, M and Bao, Y (2017) 'Linear transformation models for censored data under truncation.' Journal of Statistical Planning and Inference. ISSN 0378-3758

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Abstract

In many observational cohort studies, a pair of correlated event times are usually observed for each individual. This paper develops a new approach for the semi-parametric linear transformation model to handle the bivariate survival data under both truncation and censoring. By incorporating truncation, the potential referral bias in practice is taken into account. A class of generalised estimating equations are proposed to obtain unbiased estimates of the regression parameters. Large sample properties of the proposed estimator are provided. Simulation studies under different scenarios and analyses of real-world datasets are conducted to assess the performance of the proposed estimator

Item Type: Article
Uncontrolled Keywords: Linear Transformation model, bivariate survival function, truncation, censoring, survival analysis
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Science and Health > Mathematical Sciences, Department of
Depositing User: Elements
Date Deposited: 05 Sep 2017 12:52
Last Modified: 02 Sep 2019 21:15
URI: http://repository.essex.ac.uk/id/eprint/20291

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