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Article
Data sources: zbMATH Open
Biometrika
Article . 1995 . Peer-reviewed
Data sources: Crossref
Biometrika
Article . 1995 . Peer-reviewed
Data sources: Crossref
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Analysis of Transformation Models with Censored Data

Analysis of transformation models with censored data
Authors: Cheng, S. C.; Wei, L. J.; Ying, Z.;

Analysis of Transformation Models with Censored Data

Abstract

Summary: We consider a class of semi-parametric transformation models, under which an unknown transformation of the survival time is linearly related to the covariates with various completely specified error distributions. This class of regression models includes the proportional hazards and proportional odds models. Inference procedures derived from a class of generalised estimating equations are proposed to examine the covariate effects with censored observations. Numerical studies are conducted to investigate the properties of our proposals for practical sample sizes. These transformation models, coupled with the new simple inference procedures, provide many useful alternatives to the Cox regression model in survival analysis.

Keywords

Asymptotic distribution theory in statistics, martingale, generalised estimating equations, proportional odds models, proportional hazards, Applications of statistics to biology and medical sciences; meta analysis, survival analysis, censored observations, semi-parametric transformation models, completely specified error distributions, U-statistics, covariate effects, Nonparametric estimation

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
319
Top 1%
Top 0.1%
Average
Beta
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