Model diagnostics for multi-state models.

Titman, Andrew C. and Sharples, Linda D. (2009) Model diagnostics for multi-state models. Statistical Methods in Medical Research. ISSN 1477-0334

Full text not available from this repository.


Multi-state models are a popular method of describing medical processes that can be represented as discrete states or stages. They have particular use when the data are panel-observed, meaning they consist of discrete snapshots of disease status at irregular time points which may be unique to each patient. However, due to the difficulty of inference in more complicated cases, strong assumptions such as the Markov property, patient homogeneity and time homogeneity are applied. It is important that the validity of these assumptions is tested. A review of methods for diagnosing model fit for panel-observed continuous-time Markov and misclassification-type hidden Markov models is given, with illustrative application to a dataset on cardiac allograft vasculopathy progression in post-heart transplant patients.

Item Type:
Journal Article
Journal or Publication Title:
Statistical Methods in Medical Research
Uncontrolled Keywords:
ID Code:
Deposited By:
Deposited On:
05 Aug 2009 12:24
Last Modified:
21 Nov 2022 19:27