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• W2102128226 abstract "This paper extends the induced smoothing procedure of Brown & Wang (2006) for the semiparametric accelerated failure time model to the case of clustered failure time data. The resulting procedure permits fast and accurate computation of regression parameter estimates and standard errors using simple and widely available numerical methods, such as the Newton–Raphson algorithm. The regression parameter estimates are shown to be strongly consistent and asymptotically normal; in addition, we prove that the asymptotic distribution of the smoothed estimator coincides with that obtained without the use of smoothing. This establishes a key claim of Brown & Wang (2006) for the case of independent failure time data and also extends such results to the case of clustered data. Simulation results show that these smoothed estimates perform as well as those obtained using the best available methods at a fraction of the computational cost." @default.
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• W2102128226 date "2009-06-25" @default.
• W2102128226 modified "2023-09-30" @default.
• W2102128226 title "Induced smoothing for the semiparametric accelerated failure time model: asymptotics and extensions to clustered data" @default.
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• W2102128226 doi "https://doi.org/10.1093/biomet/asp025" @default.
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