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In this vignette we will demo how to visualize data which is only available in summary format as it is coming from a published paper table or figure for example Figure 3 from this paper:
“Remdesivir for the Treatment of Covid-19 — Final Report”
The data has been made available in a csv data file named
remdesivirfig3.csv
library(ggquickeda) #load ggquickeda
remdesivirdata <- read.csv("./remdesivirfig3.csv") # in vignette folder
knitr::kable(remdesivirdata)
Subgroup | Subgroupvalue | Subgroupvalueorder | N.of.patients | Recovery.Rate.Ratio | RRLCI | RRUCI |
---|---|---|---|---|---|---|
All Patients | 1 | 1062 | 1.29 | 1.12 | 1.49 | |
Geographic Region | North America | 2 | 847 | 1.30 | 1.10 | 1.53 |
Geographic Region | Europe | 3 | 163 | 1.30 | 0.91 | 1.87 |
Geographic Region | Asia | 4 | 52 | 1.36 | 0.74 | 2.47 |
Race | White | 5 | 566 | 1.29 | 1.06 | 1.57 |
Race | Black | 6 | 226 | 1.25 | 0.91 | 1.72 |
Race | Asian | 7 | 135 | 1.07 | 0.73 | 1.58 |
Race | Other | 8 | 135 | 1.68 | 1.10 | 2.58 |
Ethnic group | Hispanic or Latino | 9 | 250 | 1.28 | 0.94 | 1.73 |
Ethnic group | Not Hispanic or Latino | 10 | 755 | 1.31 | 1.10 | 1.55 |
Age | 18 to < 40 yr | 11 | 119 | 1.95 | 1.28 | 2.97 |
Age | 40 to < 65 yr | 12 | 559 | 1.19 | 0.98 | 1.44 |
Age | >= 65 yr | 13 | 384 | 1.29 | 1.00 | 1.67 |
Sex | Male | 14 | 684 | 1.30 | 1.09 | 1.56 |
Sex | Female | 15 | 278 | 1.31 | 1.03 | 1.66 |
Symptoms duration | <= 10 days | 16 | 676 | 1.37 | 1.14 | 1.64 |
Symptoms duration | > 10 days | 17 | 383 | 1.20 | 0.94 | 1.52 |
Baseline Ordinal Score | 4 (not receiving oxygen) | 18 | 138 | 1.29 | 0.91 | 1.83 |
Baseline Ordinal Score | 5 (receiving oxygen) | 19 | 435 | 1.45 | 1.18 | 1.79 |
Baseline Ordinal Score | 6 (receiving high-flow oxygen) | 20 | 193 | 1.09 | 0.76 | 1.57 |
Baseline Ordinal Score | 7 (receiving mv or ECMO) | 21 | 285 | 0.98 | 0.70 | 1.36 |
We still have to set text formatting options using the group of subtabs in the lower part of the page:
At this point you should have this graph:
While you can add another variable and manually drag and drop we will demo next another possibility to reorder yvalues using a statistic (e.g. median) of another variable (Subroupvalueorder):
And now you should get the below plot !:
ggquickeda
As an example of even more advanced features consider the screenshot below where the Intervals Values are shown while the point Size is proportional to the N of patients. Some theme adjustments to customize the plot and legend were also done.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.