Just to follow up on the fascinating results discussed during the population-level estimation workgroup meeting yesterday, I've generated this plot:
It simply shows the number of visits on each day divided by the number of people whose observation period included that day (in a US insurance claims DB). @Andrew: this graph shows the variations as a function of calendar time I was referring to, and the reason why matching on calendar time makes sense. Medical events are far more likely to be recorded on some calendar days than others, and failure to adjust for this could lead to (time-varying) bias. Some things worth pursuing are: distinguishing between weekdays and weekends in the SCCS, and matching subjects on day of the week (in addition to the propensity score) in a new-user cohort design.
I remember @Patrick_Ryan and I once generating similar plots, but showing days relative to birth and death instead of calendar time, which were equally revealing. Perhaps a nice topic for a paper?