Misclassification Simulation Extrapolation Method for a Weibull Accelerated Failure Time Model
Document Type
Article
Publication Date
4-25-2023
Publication Title
Statistical Methods in Medical Research
DOI
10.1177/0962280223116824
Abstract
The problem of misclassification in covariates is ubiquitous in survival data and often leads to biased estimates. The misclassification simulation extrapolation method is a popular method to correct this bias. However, its impact on Weibull accelerated failure time models has not been studied. In this paper, we study the bias caused by misclassification in one or more binary covariates in Weibull accelerated failure time models and explore the use of the misclassification simulation extrapolation in correcting for this bias, along with its asymptotic properties. Simulation studies are carried out to investigate the numerical properties of the resulting estimator for finite samples. The proposed method is then applied to colon cancer data obtained from the cancer registry at Memorial Sloan Kettering Cancer Center.
Recommended Citation
Sevilimedu, Varadan, Lili Yu, Hani Samawi.
2023.
"Misclassification Simulation Extrapolation Method for a Weibull Accelerated Failure Time Model."
Statistical Methods in Medical Research: SAGE Journals.
doi: 10.1177/0962280223116824
https://digitalcommons.georgiasouthern.edu/bee-facpubs/389
Comments
Georgia Southern University faculty members, Lili Yu and Hani Samawi co-authored Misclassification Simulation Extrapolation Method for a Weibull Accelerated Failure Time Model.