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Plot Simulation vs Real usage considering uncertainty #1025
Plot Simulation vs Real usage considering uncertainty #1025
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… levels is calculated before confidence level calculation, for Simulation
… levels is calculated before confidence level calculation, for Real
…pt is only for paper use, not for TLO, as IPAdmission already include Discharges)
Thanks Bingling --- these are really useful to look at and it's helped me to understand the effect of adjustment in greater depth too. I am thinking the following:
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Thanks Tim @tbhallett. I very much agree with your points here. So, I would
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Perfect - thanks @BinglingICL |
Thanks so much @BinglingICL Two more tiny suggestions from me-- but apart from this I am 100% ready to merge this and use them.
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Thanks for the advice Tim @tbhallett. In figure 5, did you mean to make bars to come from y = 1.0 line? I wonder if you have any quick idea to do that? These are all positive bars and seem different from stem plots as in plot (1)... Thanks. |
Sorry -- yes, I did mean y=1.0 and log scale. So, some bars go down and some go up (from 1.0), like you have in the other plots. |
Thanks Tim. Below is the one I tried to plot: I feel it looks somehow weird, as not clear as the one without log scale or starting from y=1.0? How do you think? If you would prefer a format like plots (1)-(3), I could make a similar plot (5) for only Unadjusted Data as plot (3) has already covered Adjusted Data. If to step back, considering that plot (5) is an appendix and that we would like clear information, I might prefer the previous version of plot (5): Would love to know your thoughts. And if you think the new one is alright, would be very happy to incorporate it to the branch : ) (Sorry for my weird feeling.) |
In this branch, we have tried to add more plots that consider uncertainty of usage on appointments.
From simulation side, or model side, we consider the uncertainty from different runs for each draw, i.e., mean of years 2015-2019 with 95% confidence interval.
From real data side, we consider the uncertainty w.r.t. ajustment methods (see our paper on The Changes in Health Service Utilisation in Malawi during the COVID-19 Pandemic):
(1) adjusted, DHIS2 data (2015-2019) are appropriately adjusted considering reporting rates and comparability with published data/reports
(2) unadjusted, no adjustment method is applied to the data.
As a compromise, we treat "adjusted" as the "upper" bound, "unadjusted" as the "lower" bound, and the average of "adjusted" and "unadjusted" as the "mean" for real data.