Accelerated failure-time model with weighted least-squares estimation: application on survival of HIV positives.

ABSTRACT:

Background

Survival analysis is the most appropriate method of analysis for time-to-event data. The classical accelerated failure-time model is a more powerful and interpretable model than the Cox proportional hazards model, provided that model imposed distribution and homoscedasticity assumptions satisfied. However, most of the real data are heteroscedastic which violates the fundamental assumption and consequently, the statistical inference could be erroneous in accelerated failure-time modeling. The weighted least-squares estimation for the accelerated failure-time model is an efficient semi-parametric approach for time-to-event data without the homoscedasticity assumption, which is developed recently and not often utilized for real data analysis. Thus, this study was conducted

SUBMITTER: Mustefa YA 

PROVIDER: S-EPMC8165794 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature