Induced smoothing for rank regression with censored survival times

Brown, B.M. & Wang, You-Gan (2007) Induced smoothing for rank regression with censored survival times. Statistics in Medicine, 26(4), pp. 828-836.

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Adaptions of weighted rank regression to the accelerated failure time model for censored survival data have been successful in yielding asymptotically normal estimates and flexible weighting schemes to increase statistical efficiencies. However, for only one simple weighting scheme, Gehan or Wilcoxon weights, are estimating equations guaranteed to be monotone in parameter components, and even in this case are step functions, requiring the equivalent of linear programming for computation. The lack of smoothness makes standard error or covariance matrix estimation even more difficult. An induced smoothing technique overcame these difficulties in various problems involving monotone but pure jump estimating equations, including conventional rank regression. The present paper applies induced smoothing to the Gehan-Wilcoxon weighted rank regression for the accelerated failure time model, for the more difficult case of survival time data subject to censoring, where the inapplicability of permutation arguments necessitates a new method of estimating null variance of estimating functions. Smooth monotone parameter estimation and rapid, reliable standard error or covariance matrix estimation is obtained.

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18 citations in Scopus
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15 citations in Web of Science®

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ID Code: 90519
Item Type: Journal Article
Refereed: Yes
Keywords: accelerated failure time model, censored data, covariance estimates, Gehan-Wilcoxon estimates, induced smoothing, monotone estimating, functions, rank regression, standard errors
DOI: 10.1002/sim.2576
ISSN: 0277-6715
Divisions: Current > QUT Faculties and Divisions > Science & Engineering Faculty
Deposited On: 18 Nov 2015 01:25
Last Modified: 18 Nov 2015 01:25

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