Analysis of censored and incomplete survival data using flowgraph models |
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| Authors: | Yau C Lillian Huzurbazar Aparna V |
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| Affiliation: | Department of Mathematics and Statistics, University of New Mexico, Albuquerque, NM 87131-1141, USA. |
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| Abstract: | Multi-state stochastic models are widely used to model stages of disease progression in survival analysis. This paper develops flowgraph models for data analysis in survival analysis. We illustrate these methods using data from a study of diabetic retinopathy consisting of 277 subjects with insulin-dependent (type I) diabetes mellitus (IDDM). These data were collected at the Eye-Kidney Clinic of the Barbara Davis Center for Childhood Diabetes at the University of Colorado Health Sciences Center. |
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| Keywords: | diabetic retinopathy multi‐state model recurrent event saddlepoint approximations semi‐Markov model time‐to‐event data unrecognizable incomplete data |
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