Results 211 to 220 of about 124,031 (252)

Modelling Accelerated Failure Time with a Dirichlet Process

Biometrika, 1988
The relationship between survival times \(T=(T_ 1,...,T_ n)\) and covariates \(x_ i=(1,x_{i1},...,x_{ip})\) is modelled via the accelerated failure time model \(T_ i=\exp (-x_ i\beta)V_ i,\) where \(\beta\) is a vector of fixed unknown regression coefficients, and \(V\equiv (V_ 1,...,V_ n)\) is a random sample of size n from some distribution P.
Christensen, Ronald, Johnson, Wesley
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Using Frailties in the Accelerated Failure Time Model

Lifetime Data Analysis, 2001
The accelerated failure time (AFT) model is an important alternative to the Cox proportional hazards model (PHM) in survival analysis. For multivariate failure time data we propose to use frailties to explicitly account for possible correlations (and heterogeneity) among failure times. An EM-like algorithm analogous to that in the frailty model for the
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Accelerated failure time modeling via nonparametric mixtures

Biometrics, 2021
AbstractAn accelerated failure time (AFT) model assuming a log‐linear relationship between failure time and a set of covariates can be either parametric or semiparametric, depending on the distributional assumption for the error term. Both classes of AFT models have been popular in the analysis of censored failure time data.
Byungtae Seo, Sangwook Kang
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ℓ0-Regularized high-dimensional accelerated failure time model

Computational Statistics & Data Analysis, 2022
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Chao Cheng, Xingdong Feng, Jian Huang 0003, Yuling Jiao, Shuang Zhang   +4 more
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Robust estimation in accelerated failure time models

Lifetime Data Analysis, 2018
The accelerated failure time model is widely used for analyzing censored survival times often observed in clinical studies. It is well-known that the ordinary maximum likelihood estimators of the parameters in the accelerated failure time model are generally sensitive to potential outliers or small deviations from the underlying distributional ...
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Calibration of Proportional Hazards and Accelerated Failure Time Models

Communications in Statistics - Simulation and Computation, 2012
Given a prognostic model based on one population, one may ask: Can this model be used to accurately predict disease in a different population? When the underlying rate of disease differs in the new population, the model must be calibrated. van Houwelingen (2000) considered this calibration problem focusing on proportional hazards models.
Jeannette Simino, M. Hollander, Daniel McGee   +2 more
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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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Accelerated Failure Time Models For Load Sharing Systems

IEEE Transactions on Reliability, 2014
We model the load sharing phenomenon in a k-out-of- m system through the accelerated failure time model. This model leads to multivariate families of distributions for ordered random variables, which are particular cases of the sequential order statistics.
Santosh S. Sutar, U. V. Naik-Nimbalkar
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ACCELERATED FAILURE TIME MODELS WITH NONLINEAR COVARIATES EFFECTS

Australian & New Zealand Journal of Statistics, 2007
SummaryAs a flexible alternative to the Cox model, the accelerated failure time (AFT) model assumes that the event time of interest depends on the covariates through a regression function. The AFT model with non‐parametric covariate effects is investigated, when variable selection is desired along with estimation.
Leng, C., Ma, S.
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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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