title: Attributable fraction functions for censored event times.
abstract: Attributable fractions are commonly used to measure the impact of risk factors on disease incidence in the population. These static measures can be extended to functions of time when the time to disease occurrence or event time is of interest. The present paper deals with nonparametric and semiparametric estimation of attributable fraction functions for cohort studies with potentially censored event time data. The semiparametric models include the familiar proportional hazards model and a broad class of transformation models. The proposed estimators are shown to be consistent, asymptotically normal and asymptotically efficient. Extensive simulation studies demonstrate that the proposed methods perform well in practical situations. A cardiovascular health study is provided. Connections to causal inference are discussed.
authors: Department of Biostatistics, CB# 7420 , University of North Carolina , Chapel Hill, North Carolina 27599-7420 , U.S.A. lchen@bios.unc.edu lin@bios.unc.edu dzeng@bios.unc.edu.
authors: Li
authors: L
authors: Chen
authors: D Y
authors: DY
authors: Lin
authors: Donglin
authors: D
authors: Zeng
keywords: Adjusted attributable fraction; Attributable risk; Cohort study; Population attributable fraction; Proportional hazards model; Transformation model
references: Am J Epidemiol. 2004 Feb 1;159(3):232-41
references: 14742283
references: Biometrics. 2001 Mar;57(1):182-8
references: 11252596
references: Stat Med. 1982 Jul-Sep;1(3):229-43
references: 7187096
references: Biostatistics. 2006 Oct;7(4):515-29
references: 16478758
references: Stat Methods Med Res. 2001 Jun;10(3):195-216
references: 11446148
references: Acta Unio Int Contra Cancrum. 1953;9(3):531-41
references: 13124110
references: Biometrics. 1996 Mar;52(1):137-51
references: 8934589
references: Biometrics. 2005 Sep;61(3):847-55
references: 16135037
references: Ann Epidemiol. 1991 Feb;1(3):263-76
references: 1669507
references: Am J Epidemiol. 1985 Nov;122(5):904-14
references: 4050778