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Brief introduction to parametric time to event model

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Abstract
This tutorial explains the basic concept of parametric time to event (TTE) models, focusing on commonly used exponential, Weibull, and log-logistic model. TTE data is commonly used as endpoint for treatment effect of a drug or prognosis of diseases. Although non-parametric Kaplan-Meier analysis has been widely used for TTE data analysis, parametric modeling analysis has its own advantages such as ease of simulation, and evaluation of continuous covariate. Accelerated failure time model is introduced as a covariate model for TTE data together with proportional hazard model. Compared to proportional hazard model, accelerated failure time model provides more intuitive results on covariate effect since it states that covariates change TTE whereas in proportional hazard model covariates affect hazard.
Author(s)
임형석
Issued Date
2021
Type
Article
Keyword
Accelerated Failure Time ModelParametric Time to Event ModelProportional Hazard Model
DOI
10.12793/tcp.2021.29.e7
URI
https://oak.ulsan.ac.kr/handle/2021.oak/7693
https://ulsan-primo.hosted.exlibrisgroup.com/primo-explore/fulldisplay?docid=TN_cdi_nrf_kci_oai_kci_go_kr_ARTI_9876341&context=PC&vid=ULSAN&lang=ko_KR&search_scope=default_scope&adaptor=primo_central_multiple_fe&tab=default_tab&query=any,contains,Brief%20introduction%20to%20parametric%20time%20to%20event%20model&offset=0&pcAvailability=true
Publisher
Translational and Clinical Pharmacology
Location
대한민국
Language
영어
ISSN
2289-0882
Citation Volume
29
Citation Number
1
Citation Start Page
1
Citation End Page
5
Appears in Collections:
Medicine > Medicine
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