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