According to multilevel(/mixed) modelling texts, it is fine to include clusters with only one observation. However, when applying these models to repeated-measure data to explore change over time, including individuals with one data-point seem counterintuitive: how can change be modelled with one data-point?
What are the problems, if any, of including such individuals when using mixed models for change over time? Should they be excluded? Is this different for GEE, which is said to be for “population” rather than individual estimates?