Results 251 to 260 of about 628,696 (290)

Accelerated failure time models for counting processes

Biometrika, 1998
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Lin, D. Y., Wei, L. J., Ying, Zhiliang
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Accelerated failure time model with quantile information

Annals of the Institute of Statistical Mathematics, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Zhao, Mu, Wang, Yixin, Zhou, Yong
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Covariate selection for accelerated failure time data

Communications in Statistics - Theory and Methods, 2016
ABSTRACTSelection of appropriate predictors for right censored time to event data is very often encountered by the practitioners. We consider the l1 penalized regression or “least absolute shrinkage and selection operator” as a tool for predictor selection in association with accelerated failure time model.
Ujjwal Das, Nader Ebrahimi
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Nonparametric Analysis of an Accelerated Failure Time Model

Biometrika, 1981
SUMMARY Survival distributions can be characterized by and compared through their hazard functions. Tests using a proportional hazards model have good power if the two hazards do not cross, but without time-dependent covariates can have low power if they do.
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Rank-based inference for the accelerated failure time model

Biometrika, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Jin, Zhezhen, Lin, D. Y., Wei, L. J., Ying, Zhiliang   +3 more
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Analysis of Failure Time Data with Mixed-Effects Accelerated Failure Time Model

Communications in Statistics - Simulation and Computation, 2011
In randomized clinical trials or observational studies, subjects are recruited at multiple treating sites. Factors that vary across sites may have some influence on outcomes; therefore, they need to be taken into account to get better results. We apply the accelerated failure time (AFT) model with linear mixed effects to analyze failure time data ...
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Accelerated Failure Time Models

2023
Ton J. Cleophas, Aeilko H. Zwinderman
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Accelerated Failure Time Models with Auxiliary Covariates

Journal of Biometrics & Biostatistics, 2012
In this paper we study semi-parametric inference procedure for accelerated failure time models with auxiliary information about a main exposure variable. We use a kernel smoothing method to introduce the auxiliary covariate to the likelihood function. The regression parameters are then estimated through maximization of the estimated likelihood function.
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Weighted accelerated failure time model

The accelerated failure time (AFT) model is widely used in survival analysis and auxiliary information can be used to improve the efficiency of the model. We developed a weighted AFT model by using empirical likelihood probabilities as weights based on information from previous studies. The proposed model effectively overcomes the challenges associated
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G-estimation for Accelerated Failure Time Models

2012
In this chapter we examine the problem of time-varying confounding, and one method (structural nested accelerated failure time models, estimated using and also known as g-estimation) which may be used to overcome it. A practical example is given, and the methodology demonstrated.
Kate Tilling, Jonathan A. C. Sterne, Vanessa Didelez   +2 more
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