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Survival analysis of time‐to‐event data in respiratory health research studies
Author(s) -
Kasza Jessica,
Wraith Darren,
Lamb Karen,
Wolfe Rory
Publication year - 2014
Publication title -
respirology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.857
H-Index - 85
eISSN - 1440-1843
pISSN - 1323-7799
DOI - 10.1111/resp.12281
Subject(s) - medicine , respiratory system , event (particle physics) , event data , intensive care medicine , environmental health , emergency medicine , data mining , analytics , physics , quantum mechanics , computer science
This article provides a review of techniques for the analysis of survival data arising from respiratory health studies. Popular techniques such as the K aplan– M eier survival plot and the C ox proportional hazards model are presented and illustrated using data from a lung cancer study. Advanced issues are also discussed, including parametric proportional hazards models, accelerated failure time models, time‐varying explanatory variables, simultaneous analysis of multiple types of outcome events and the restricted mean survival time, a novel measure of the effect of treatment.