Analysis of failure time using threshold regression with semi‐parametric varying coefficients |
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Authors: | Jialiang Li Mei‐Ling Ting Lee |
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Affiliation: | 1. Department of Statistics and Applied Probability, Duke‐NUS Graduate Medical School, National University of Singapore;2. Department of Epidemiology and Biostatistics, Biostatistics and Risk Assessment Center, School of Public Health, University of Maryland |
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Abstract: | Many new statistical models may enjoy better interpretability and numerical stability than traditional models in survival data analysis. Specifically, the threshold regression (TR) technique based on the inverse Gaussian distribution is a useful alternative to the Cox proportional hazards model to analyse lifetime data. In this article we consider a semi‐parametric modelling approach for TR and contribute implementational and theoretical details for model fitting and statistical inferences. Extensive simulations are carried out to examine the finite sample performance of the parametric and non‐parametric estimates. A real example is analysed to illustrate our methods, along with a careful diagnosis of model assumptions. |
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Keywords: | threshold regression Wiener process varying coefficients model inverse Gaussian distribution bootstrap |
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