Hello R users!
I am a medic and have been working with R for about 6 months now.
I was hoping to pick someones brain about a diagnostic accuracy study that has
now been completed.
I am trying to derive the sensitivity, specificity, NPV and PPV with the
corresponding 95% CI from the raw data.
My data is in a data frame as below
g.s t1 t2 t3 t3 t4 t5 index
Yes 1 1 1 1 1 1 1
Yes 1 1 1 1 1 1 2
Yes 1 1 1 1 1 1 3
Yes 1 1 1 1 1 1 4
Yes 1 1 1 1 1 1 5
Each row represents a patient with a unique id (variable: index).
g.s is a binary variable ans represents the results from the gold standard (yes
/ no).
t1 to t5 are the tests at different thresholds being tested.
t1 to t5 are all binary variables with 1 as yes and 0 as no.
Now i could create separate 2 x 2 tables for each threshold (t1 to t5) against
the gold standard and subsequently derive sense, spec, NPV and PPV plus their
95 % CI for each threshold (t1 to t5).
I was however wondering if there was a more efficient way to get these results
from the raw data in R.
Hope I have explained my self clearly and thanks a lot in advance!!
Cheers
Anoop
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