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is cfr_rolling()
suitable for small time-series and cfr_time_varying()
for larget ones?
#123
Comments
Thanks @avallecam - the two functions are aimed at providing different functionalities.
|
Useful clarification.
About the different trends that we get from the two methods, any suggestions about how to discuss it? |
I think the key is to discuss the static and time varying methods and where they apply. The rolling method is perhaps more useful to check whether an outbreak's CFR estimate has stabilised. The rolling and time-varying methods aren't really comparable, so I wouldn't really discuss them together. Is it worth mentioning some reasons not to interpret the rolling estimate in relation to the time-varying one? |
Perhaps a useful rule of thumb is to discuss in context of the sampling uncertainy. E.g. With 100 cases, the fatality risk estimate will, roughly speaking, have a 95% confidence interval ±10% of the mean estimate (binomial CI). So if we have >100 cases with expected outcomes on a given day, we can get reasonable estimates of the time varying CFR. But if we only have >100 cases over the course of the whole epidemic, we probably need to rely on the static version that uses the cumulative data. |
Thanks @adamkucharski! @avallecam, did you have any specific suggestions for where these clarifications should be added? |
In the tutorial episode drafted, we include the clarifications shared here. Please, see that section in the working branch (edit suggestions welcome in working PR). At the end, we refer to the vignette on Although this outbreak size detail is mentioned briefly in the get started vignette, probably it would be informative to complement the current vignette showing that point in particular, on how the time-varying method performs under different sizes of cases per day (then, our reference from tutorials to vignette could be more specific). If this content gets too long, we can consider another vignette. If appropriate, this could be based on the reprex above. |
Closed as answered, and this will be addressed by #128 |
From documentation:
However, I do not find a specific reference to a difference or direct comparison between
cfr_rolling()
andcfr_time_varying()
.From reprex-es below, I find that:
cfr_rolling()
is more suited toebola1976
(small time-series), whilecfr_time_varying()
is more suited tocovid_data
(larger time-series).Can I conclude that
cfr_rolling()
would be useful for real-time estimations, whilecfr_time_varying()
for retrospective assessments?small outbreak time-series
Created on 2024-01-31 with reprex v2.0.2
large outbreak time-series
Created on 2024-01-31 with reprex v2.0.2
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