Model diagnostics for multi-state models

Titman and Sharples have a new review paper in SMMR. This considers methods for assessing fit in parametric, panel observed multi-state models. The primary focus is on the assessment of time homogeneous Markov models, although there is also a section on hidden Markov models that occur if states are considered to be observed with classification error. Methods for fitting more complicated models such as non-homogeneous and random effects models are also reviewed. A simple graphical generalization of the prevalence counts method of Gentleman et al (Stats in Med, 1994) is also developed.