Smoothed rank regression with censored data Journal Article


Author: Heller, G.
Article Title: Smoothed rank regression with censored data
Abstract: A weighted rank estimating function is proposed to estimate the regression parameter vector in an accelerated failure time model with right censored data. In general, rank estimating functions are discontinuous in the regression parameter, creating difficulties in determining the asymptotic distribution of the estimator. A local distribution function is used to create a rank based estimating function that is continuous and monotone in the regression parameter vector. A weight is included in the estimating function to produce a bounded influence estimate. The asymptotic distribution of the regression estimator is developed and simulations are performed to examine its finite sample properties. A lung cancer dataset is used to illustrate the methodology. © 2007 American Statistical Association.
Keywords: bounded influence function; local distribution function; monotone estimating equation; u statistic
Journal Title: Journal of the American Statistical Association
Volume: 102
Issue: 478
ISSN: 0162-1459
Publisher: American Statistical Association  
Date Published: 2007-06-01
Start Page: 552
End Page: 559
Language: English
DOI: 10.1198/016214506000001257
PROVIDER: scopus
DOI/URL:
Notes: --- - "Cited By (since 1996): 3" - "Export Date: 17 November 2011" - "Source: Scopus"
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  1. Glenn Heller
    399 Heller