3 ms·
One feels that, irrespective of the models, the data in the covid-19 case may be unusually bad. It may be time to add a third error category[1] I. False posit
by smitty1e 7y ago
One feels that, irrespective of the models, the data in the covid-19 case may be unusually bad.
It may be time to add a third error category[1]
I. False positive
II. False negative
III. Deliberately skewed off the map for propaganda reasons.
[1] https://en.m.wikipedia.org/wiki/Type_I_and_type_II_errors#Type_II_error https://en.m.wikipedia.org/wiki/Type_I_and_type_II_errors#Ty...
- YZF 7y agoThis is driving me crazy ;) the poor quality of data. You'd want health organizations around the world to be publishing every possible detail (anonymized) so that the disease can be better understood. Yet three months in, with over a million cases worldwide, we still have experts disagreeing about things like asymptomatic transmission, use of masks, droplets vs. aerosol, how much distance one should stand from another, viability on surfaces, etc. etc. Even for treatment options rather than insisting on randomized double blind trials start by using the natural experiments that are already happening. We should have the data to answer a lot of these questions (or at least draw out some probability distributions), or at least someone has it. This stuff is going to be critical in informing exit strategies.
- magoghm 7y agoMy experience with data is: you never get good data. Always, the closer you look at it the more problems you find in how it was collected.
- thaumasiotes 7y ago> You'd want health organizations around the world to be publishing every possible detail (anonymized) If you're publishing every possible detail, then your data isn't anonymized. Anonymization consists of the removal of almost all of the details.
- smitty1e 7y agoOr even if the data are reasonably tidy, they might expose more when juxtaposed with another dataset.