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(v1.3.0.9035) mdro() for EUCAST 3.2, examples cleanup

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dr. M.S. (Matthijs) Berends
2020-09-29 23:35:46 +02:00
parent 68e6e1e329
commit 4e0374af29
94 changed files with 1143 additions and 1165 deletions
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88
man/first_isolate.Rd
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@ -98,15 +98,16 @@ To conduct an analysis of antimicrobial resistance, you should only include the
All isolates with a microbial ID of \code{NA} will be excluded as first isolate.
The functions \code{\link[=filter_first_isolate]{filter_first_isolate()}} and \code{\link[=filter_first_weighted_isolate]{filter_first_weighted_isolate()}} are helper functions to quickly filter on first isolates. The function \code{\link[=filter_first_isolate]{filter_first_isolate()}} is essentially equal to one of:\preformatted{ x \%>\% filter(first_isolate(., ...))
The functions \code{\link[=filter_first_isolate]{filter_first_isolate()}} and \code{\link[=filter_first_weighted_isolate]{filter_first_weighted_isolate()}} are helper functions to quickly filter on first isolates. The function \code{\link[=filter_first_isolate]{filter_first_isolate()}} is essentially equal to either:\preformatted{ x[first_isolate(x, ...), ]
x \%>\% filter(first_isolate(x, ...))
}
The function \code{\link[=filter_first_weighted_isolate]{filter_first_weighted_isolate()}} is essentially equal to:\preformatted{ x \%>\%
mutate(keyab = key_antibiotics(.)) \%>\%
mutate(only_weighted_firsts = first_isolate(x,
col_keyantibiotics = "keyab", ...)) \%>\%
filter(only_weighted_firsts == TRUE) \%>\%
select(-only_weighted_firsts, -keyab)
The function \code{\link[=filter_first_weighted_isolate]{filter_first_weighted_isolate()}} is essentially equal to:\preformatted{ x \%>\%
mutate(keyab = key_antibiotics(.)) \%>\%
mutate(only_weighted_firsts = first_isolate(x,
col_keyantibiotics = "keyab", ...)) \%>\%
filter(only_weighted_firsts == TRUE) \%>\%
select(-only_weighted_firsts, -keyab)
}
}
\section{Key antibiotics}{
@ -139,49 +140,40 @@ On our website \url{https://msberends.github.io/AMR} you can find \href{https://
# `example_isolates` is a dataset available in the AMR package.
# See ?example_isolates.
\dontrun{
library(dplyr)
# Filter on first isolates:
example_isolates \%>\%
mutate(first_isolate = first_isolate(.)) \%>\%
filter(first_isolate == TRUE)
# basic filtering on first isolates
example_isolates[first_isolate(example_isolates), ]
# Now let's see if first isolates matter:
A <- example_isolates \%>\%
group_by(hospital_id) \%>\%
summarise(count = n_rsi(GEN), # gentamicin availability
resistance = resistance(GEN)) # gentamicin resistance
B <- example_isolates \%>\%
filter_first_weighted_isolate() \%>\% # the 1st isolate filter
group_by(hospital_id) \%>\%
summarise(count = n_rsi(GEN), # gentamicin availability
resistance = resistance(GEN)) # gentamicin resistance
# Have a look at A and B.
# B is more reliable because every isolate is counted only once.
# Gentamicin resistance in hospital D appears to be 3.7\% higher than
# when you (erroneously) would have used all isolates for analysis.
## OTHER EXAMPLES:
# Short-hand versions:
example_isolates \%>\%
filter_first_isolate()
\donttest{
if (require("dplyr")) {
# Filter on first isolates:
example_isolates \%>\%
mutate(first_isolate = first_isolate(.)) \%>\%
filter(first_isolate == TRUE)
# Short-hand versions:
example_isolates \%>\%
filter_first_isolate()
example_isolates \%>\%
filter_first_weighted_isolate()
example_isolates \%>\%
filter_first_weighted_isolate()
# set key antibiotics to a new variable
x$keyab <- key_antibiotics(x)
x$first_isolate <- first_isolate(x)
x$first_isolate_weighed <- first_isolate(x, col_keyantibiotics = 'keyab')
x$first_blood_isolate <- first_isolate(x, specimen_group = "Blood")
# Now let's see if first isolates matter:
A <- example_isolates \%>\%
group_by(hospital_id) \%>\%
summarise(count = n_rsi(GEN), # gentamicin availability
resistance = resistance(GEN)) # gentamicin resistance
B <- example_isolates \%>\%
filter_first_weighted_isolate() \%>\% # the 1st isolate filter
group_by(hospital_id) \%>\%
summarise(count = n_rsi(GEN), # gentamicin availability
resistance = resistance(GEN)) # gentamicin resistance
# Have a look at A and B.
# B is more reliable because every isolate is counted only once.
# Gentamicin resistance in hospital D appears to be 3.7\% higher than
# when you (erroneously) would have used all isolates for analysis.
}
}
}
\seealso{