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Even if the data was misreported, which is a possibility, censoring or deleting it in some way is the worst option. Lets say Florid's growth for that month was
by chris11 6y ago
Even if the data was misreported, which is a possibility, censoring or deleting it in some way is the worst option. Lets say Florid's growth for that month was 30%. But because of bad reporting it thought it had a growth rate of 15%, until the end of the month when all of the missed cases were reported. That spike will not be accurate, but just deleting it would make it look like Florida still had a 15% growth rate. Reviewing the full months data to correct those issues would give the clearest report, but reporting the raw data is more honest than just deleting the anomaly.
- ImaCake 6y agoThe trade off is between measurement bias and selection bias. Typically you want to be dealing with measurement bias and not selection bias, since the latter is often impossible to account for. You are correct that it is preferable to report the raw data, but it is more than just "honest"! Even with that data `incorrectly` on the wrong day, when binned as a full month the growth rate will be correct. That is, the data is now more correct than if the late reported deaths were not included. I believe this is effectively the same as Intention to Treat Analysis (https://en.wikipedia.org/wiki/Intention-to-treat_analysis https://en.wikipedia.org/wiki/Intention-to-treat_analysis).