Wu, JingjingLu, XuewenHuang, Yifu2024-05-072024-05-072024-05-06Huang, Y. (2024). Minimum Hellinger distance estimation of AFT models with right-censored data (Master's thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca.https://hdl.handle.net/1880/118695https://doi.org/10.11575/PRISM/43537Accelerated Failure Time (AFT) models are popular models used in survival analysis. AFT models are also an important alternative to the Cox Proportional Hazards (PH) models as they have better interpretability and link the survival time (usually on the log scale) directly to the covariates. The unknown coefficient parameters in AFT models are often estimated by the maximum likelihood estimator (MLE). However, the performance of MLE would be severely affected by the presence of outliers. In this thesis, we proposed two estimators to estimate the parametric AFT models based on minimum Hellinger distance estimation (MHDE). A simulation study and a real data analysis were conducted to examine the performance of the proposed estimators under various scenarios for censoring rate and presence of outliers. Our numerical results demonstrated the excellent robustness of the proposed estimators which also retain good efficiency for many cases.enUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.Education--Mathematicsmaster thesis