Brief introduction to parametric time to event model
被引:4
作者:
Lim, Hyeong-Seok
论文数: 0引用数: 0
h-index: 0
机构:
Univ Ulsan, Asan Med Ctr, Dept Clin Pharmacol & Therapeut, Seoul 05505, South KoreaUniv Ulsan, Asan Med Ctr, Dept Clin Pharmacol & Therapeut, Seoul 05505, South Korea
Lim, Hyeong-Seok
[1
]
机构:
[1] Univ Ulsan, Asan Med Ctr, Dept Clin Pharmacol & Therapeut, Seoul 05505, South Korea
Parametric Time to Event Model;
Accelerated Failure Time Model;
Proportional Hazard Model;
D O I:
10.12793/tcp.2021.29.e7
中图分类号:
R9 [药学];
学科分类号:
1007 ;
摘要:
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.