Aspects of analysis of multivariate failure time data.

Prentice, Ross L., and Kalbfleisch, John D.. "Aspects of analysis of multivariate failure time data.." SORT 27.1 (2003): 65-78. <http://eudml.org/doc/40442>.

@article{Prentice2003,
abstract = {Multivariate failure time data arise in various forms including recurrent event data when individuals are followed to observe the sequence of occurrences of a certain type of event; correlated failure time when an individual is followed for the occurrence of two or more types of events for which the individual is simultaneously at risk, or when distinct individuals have depending event times; or more complicated multistate processes where individuals may move among a number of discrete states over the course of a follow-up study and the states and associated sojourn times are recorded. Here we provide a critical review of statistical models and data analysis methods for the analysis of recurrent event data and correlated failure time data. This review suggests a valuable role for partially marginalized intensity models for the analysis of recurrent event data, and points to the usefulness of marginal hazard rate models and nonparametric estimates of pairwise dependencies for the analysis of correlated failure times. Areas in need of further methodology development are indicated.},
author = {Prentice, Ross L., Kalbfleisch, John D.},
journal = {SORT},
keywords = {Bioestadística; Análisis de supervivencia; Estimación; Análisis multivariante; Análisis de datos censurados; correlated failure times; independent censoring; marginal models; survivor function estimation; recurrent events},
language = {eng},
number = {1},
pages = {65-78},
title = {Aspects of analysis of multivariate failure time data.},
url = {http://eudml.org/doc/40442},
volume = {27},
year = {2003},
}

TY - JOUR
AU - Prentice, Ross L.
AU - Kalbfleisch, John D.
TI - Aspects of analysis of multivariate failure time data.
JO - SORT
PY - 2003
VL - 27
IS - 1
SP - 65
EP - 78
AB - Multivariate failure time data arise in various forms including recurrent event data when individuals are followed to observe the sequence of occurrences of a certain type of event; correlated failure time when an individual is followed for the occurrence of two or more types of events for which the individual is simultaneously at risk, or when distinct individuals have depending event times; or more complicated multistate processes where individuals may move among a number of discrete states over the course of a follow-up study and the states and associated sojourn times are recorded. Here we provide a critical review of statistical models and data analysis methods for the analysis of recurrent event data and correlated failure time data. This review suggests a valuable role for partially marginalized intensity models for the analysis of recurrent event data, and points to the usefulness of marginal hazard rate models and nonparametric estimates of pairwise dependencies for the analysis of correlated failure times. Areas in need of further methodology development are indicated.
LA - eng
KW - Bioestadística; Análisis de supervivencia; Estimación; Análisis multivariante; Análisis de datos censurados; correlated failure times; independent censoring; marginal models; survivor function estimation; recurrent events
UR - http://eudml.org/doc/40442
ER -