Analysis of interval-censored disease progression data via multi-state models under a nonignorable inspection process

Chen, Yi and Cook have a new paper in Statistics in Medicine. This covers similar ground to the paper of Sweeting et al as it is also concerned with a nonignorable inspection process for a panel observed progressive Markov multi-state model. Again there are a set of known planned observation times, but unlike Sweeting et al there is no auxiliary data. A MNAR model where the missingness probability depends on the true state at the potential observation time is used. This is similar to the MNAR model in Sweeting et al, except that here piecewise constant transition intensities are used rather than a time homogeneous model. The model is fitted using an EM algorithm.

Both this study and Sweeting et al's depend on there being a known set of planned examination times. In the majority of cases, only the actual examination times are known and the observation process is not fully understood. As Chen et al note, informative observation times could be dealt with by determining a stochastic model for the observation process, but would require assumptions about the process.