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Abstract:
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Multi-state models are commonly used in studies of disease progression. Methods developed under this framework, however, are often challenged by misclassication in states. In this talk, I will discuss issues concerning continuous time progressive multi-state models with state misclassication. We develop inference methods using both the likelihood and pairwise likelihood methods that are based on joint modelling of the transition and misclassication processes. The performance of estimation procedures is evaluated by numerical studies.
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