Misclassification simulation extrapolation method for a Weibull accelerated failure time model Journal Article


Authors: Sevilimedu, V.; Yu, L.; Samawi, H.
Article Title: Misclassification simulation extrapolation method for a Weibull accelerated failure time model
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. © The Author(s) 2023.
Keywords: survival analysis; proportional hazards models; proportional hazards model; statistical analysis; data interpretation, statistical; computer simulation; measurement error; bias; misclassification; statistical bias; accelerated failure time model; weibull distribution
Journal Title: Statistical Methods in Medical Research
Volume: 32
Issue: 8
ISSN: 0962-2802
Publisher: Sage Publications  
Date Published: 2023-08-01
Start Page: 1478
End Page: 1493
Language: English
DOI: 10.1177/09622802231168248
PUBMED: 37122155
PROVIDER: scopus
PMCID: PMC10939450
DOI/URL:
Notes: Article -- Source: Scopus
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