NDLI: A maximum pseudo-profile likelihood estimator for the Cox model under length-biased sampling

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A maximum pseudo-profile likelihood estimator for the Cox model under length-biased sampling

Content Provider	PubMed Central
Author	Huang, Chiung-yu Qin, Jing Follmann, Dean A.
Copyright Year	2012
Abstract	This paper considers semiparametric estimation of the Cox proportional hazards model for right-censored and length-biased data arising from prevalent sampling. To exploit the special structure of length-biased sampling, we propose a maximum pseudo-profile likelihood estimator, which can handle time-dependent covariates and is consistent under covariate-dependent censoring. Simulation studies show that the proposed estimator is more efficient than its competitors. A data analysis illustrates the methods and theory.
Related Links	http://dx.doi.org/10.1093/biomet/asr072
Ending Page	210
Page Count	12
Starting Page	199
File Format	PDF
ISSN	00063444
e-ISSN	14643510
Journal	Biometrika
Issue Number	1
Volume Number	99
Language	English
Publisher	Oxford University Press
Publisher Date	2012-03-01
Access Restriction	Open
Rights Holder	Oxford University Press
Subject Keyword	Agricultural and Biological Sciences (miscellaneous) Statistics, Probability and Uncertainty Statistics and Probability Applied Mathematics Agricultural and Biological Sciences(all) Mathematics(all) Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Statistics and Probability Agricultural and Biological Sciences Statistics, Probability and Uncertainty

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