TY - JOUR
T1 - A quantile regression model for failure-time data with time-dependent covariates
AU - Gorfine, Malka
AU - Goldberg, Yair
AU - Ritov, Ya'acov
N1 - Publisher Copyright:
© 2016 The Author.
PY - 2017/1/1
Y1 - 2017/1/1
N2 - Since survival data occur over time, often important covariates that we wish to consider also change over time. Such covariates are referred as time-dependent covariates. Quantile regression offers flexible modeling of survival data by allowing the covariates to vary with quantiles. This article provides a novel quantile regression model accommodating time-dependent covariates, for analyzing survival data subject to right censoring. Our simple estimation technique assumes the existence of instrumental variables. In addition, we present a doubly-robust estimator in the sense of Robins and Rotnitzky (1992, Recovery of information and adjustment for dependent censoring using surrogate markers. In: Jewell, N. P., Dietz, K. and Farewell, V. T. (editors), AIDS Epidemiology. Boston: Birkhaäuser, pp. 297-331.). The asymptotic properties of the estimators are rigorously studied. Finite-sample properties are demonstrated by a simulation study. The utility of the proposed methodology is demonstrated using the Stanford heart transplant dataset.
AB - Since survival data occur over time, often important covariates that we wish to consider also change over time. Such covariates are referred as time-dependent covariates. Quantile regression offers flexible modeling of survival data by allowing the covariates to vary with quantiles. This article provides a novel quantile regression model accommodating time-dependent covariates, for analyzing survival data subject to right censoring. Our simple estimation technique assumes the existence of instrumental variables. In addition, we present a doubly-robust estimator in the sense of Robins and Rotnitzky (1992, Recovery of information and adjustment for dependent censoring using surrogate markers. In: Jewell, N. P., Dietz, K. and Farewell, V. T. (editors), AIDS Epidemiology. Boston: Birkhaäuser, pp. 297-331.). The asymptotic properties of the estimators are rigorously studied. Finite-sample properties are demonstrated by a simulation study. The utility of the proposed methodology is demonstrated using the Stanford heart transplant dataset.
KW - Instrumental variables
KW - Quantile regression
KW - Survival analysis
KW - Time-dependent covariates
UR - http://www.scopus.com/inward/record.url?scp=85021361957&partnerID=8YFLogxK
U2 - 10.1093/biostatistics/kxw036
DO - 10.1093/biostatistics/kxw036
M3 - ???researchoutput.researchoutputtypes.contributiontojournal.article???
C2 - 27485534
AN - SCOPUS:85021361957
SN - 1465-4644
VL - 18
SP - 132
EP - 146
JO - Biostatistics
JF - Biostatistics
IS - 1
ER -