You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Hi, thanks a lot for the great work you're doing. Would it be possible to add error bars in your .csv files? The CDC included an Upper Bound Threshold in their files and it would be quite helpful if you could do the same in your analysis.
The CDC error bars are based on 95% confidence intervals (see https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm). Using Gaussian error statistics, one can obtain Upper Bound Threshold via Upper Bound Threshold = Average Expected Count + 1.96*Standard Deviation.
Thanks!
The text was updated successfully, but these errors were encountered:
Maybe one could just use mutate(expected_deaths = predict(expected_deaths_model,.,interval = "confidence") in the get_excess_deaths function. The default confidence interval is the 95% CI.
Hi, thanks a lot for the great work you're doing. Would it be possible to add error bars in your
.csv
files? The CDC included anUpper Bound Threshold
in their files and it would be quite helpful if you could do the same in your analysis.The CDC error bars are based on 95% confidence intervals (see https://www.cdc.gov/nchs/nvss/vsrr/covid19/excess_deaths.htm). Using Gaussian error statistics, one can obtain
Upper Bound Threshold
viaUpper Bound Threshold = Average Expected Count + 1.96*Standard Deviation
.Thanks!
The text was updated successfully, but these errors were encountered: