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count_R and count_IR can be used to count resistant isolates, count_S and count_SI can be used to count susceptible isolates." />
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< h1 > Count isolates< / h1 >
< div class = "hidden name" > < code > count.Rd< / code > < / div >
< / div >
< div class = "ref-description" >
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< p > These functions can be used to count resistant/susceptible microbial isolates. All functions support quasiquotation with pipes, can be used in < code > dplyr< / code > s < code > < a href = 'https://dplyr.tidyverse.org/reference/summarise.html' > summarise< / a > < / code > and support grouped variables, see < em > Examples< / em > .< / p >
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< p > < code > count_R< / code > and < code > count_IR< / code > can be used to count resistant isolates, < code > count_S< / code > and < code > count_SI< / code > can be used to count susceptible isolates.< br / > < / p >
< / div >
< pre class = "usage" > < span class = 'fu' > count_R< / span > (< span class = 'no' > ...< / span > , < span class = 'kw' > also_single_tested< / span > < span class = 'kw' > =< / span > < span class = 'fl' > FALSE< / span > )
< span class = 'fu' > count_IR< / span > (< span class = 'no' > ...< / span > , < span class = 'kw' > also_single_tested< / span > < span class = 'kw' > =< / span > < span class = 'fl' > FALSE< / span > )
< span class = 'fu' > count_I< / span > (< span class = 'no' > ...< / span > , < span class = 'kw' > also_single_tested< / span > < span class = 'kw' > =< / span > < span class = 'fl' > FALSE< / span > )
< span class = 'fu' > count_SI< / span > (< span class = 'no' > ...< / span > , < span class = 'kw' > also_single_tested< / span > < span class = 'kw' > =< / span > < span class = 'fl' > FALSE< / span > )
< span class = 'fu' > count_S< / span > (< span class = 'no' > ...< / span > , < span class = 'kw' > also_single_tested< / span > < span class = 'kw' > =< / span > < span class = 'fl' > FALSE< / span > )
< span class = 'fu' > count_all< / span > (< span class = 'no' > ...< / span > )
< span class = 'fu' > n_rsi< / span > (< span class = 'no' > ...< / span > )
< span class = 'fu' > count_df< / span > (< span class = 'no' > data< / span > , < span class = 'kw' > translate_ab< / span > < span class = 'kw' > =< / span > < span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/base/topics/options' > getOption< / a > < / span > (< span class = 'st' > "get_antibiotic_names"< / span > ,
< span class = 'st' > "official"< / span > ), < span class = 'kw' > combine_IR< / span > < span class = 'kw' > =< / span > < span class = 'fl' > FALSE< / span > )< / pre >
< h2 class = "hasAnchor" id = "arguments" > < a class = "anchor" href = "#arguments" > < / a > Arguments< / h2 >
< table class = "ref-arguments" >
< colgroup > < col class = "name" / > < col class = "desc" / > < / colgroup >
< tr >
< th > ...< / th >
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< td > < p > one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with < code > < a href = 'as.rsi.html' > as.rsi< / a > < / code > if needed.< / p > < / td >
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< / tr >
< tr >
< th > also_single_tested< / th >
< td > < p > a logical to indicate whether (in combination therapies) also observations should be included where not all antibiotics were tested, but at least one of the tested antibiotics contains a target interpretation (e.g. S in case of < code > portion_S< / code > and R in case of < code > portion_R< / code > ). < strong > This would lead to selection bias in almost all cases.< / strong > < / p > < / td >
< / tr >
< tr >
< th > data< / th >
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< td > < p > a < code > data.frame< / code > containing columns with class < code > rsi< / code > (see < code > < a href = 'as.rsi.html' > as.rsi< / a > < / code > )< / p > < / td >
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< / tr >
< tr >
< th > translate_ab< / th >
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< td > < p > a column name of the < code > < a href = 'antibiotics.html' > antibiotics< / a > < / code > data set to translate the antibiotic abbreviations to, using < code > < a href = 'abname.html' > abname< / a > < / code > . This can be set with < code > < a href = 'https://www.rdocumentation.org/packages/base/topics/options' > getOption< / a > ("get_antibiotic_names")< / code > .< / p > < / td >
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< / tr >
< tr >
< th > combine_IR< / th >
< td > < p > a logical to indicate whether all values of I and R must be merged into one, so the output only consists of S vs. IR (susceptible vs. non-susceptible)< / p > < / td >
< / tr >
< / table >
< h2 class = "hasAnchor" id = "source" > < a class = "anchor" href = "#source" > < / a > Source< / h2 >
< p > Wickham H. < strong > Tidy Data.< / strong > The Journal of Statistical Software, vol. 59, 2014. < a href = 'http://vita.had.co.nz/papers/tidy-data.html' > http://vita.had.co.nz/papers/tidy-data.html< / a > < / p >
< h2 class = "hasAnchor" id = "value" > < a class = "anchor" href = "#value" > < / a > Value< / h2 >
< p > Integer< / p >
< h2 class = "hasAnchor" id = "details" > < a class = "anchor" href = "#details" > < / a > Details< / h2 >
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< p > These functions are meant to count isolates. Use the < code > < a href = 'portion.html' > portion< / a > _*< / code > functions to calculate microbial resistance.< / p >
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< p > < code > n_rsi< / code > is an alias of < code > count_all< / code > . They can be used to count all available isolates, i.e. where all input antibiotics have an available result (S, I or R). Their use is equal to < code > < a href = 'https://dplyr.tidyverse.org/reference/n_distinct.html' > n_distinct< / a > < / code > . Their function is equal to < code > count_S(...) + count_IR(...)< / code > .< / p >
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< p > < code > count_df< / code > takes any variable from < code > data< / code > that has an < code > "rsi"< / code > class (created with < code > < a href = 'as.rsi.html' > as.rsi< / a > < / code > ) and counts the amounts of R, I and S. The resulting < em > tidy data< / em > (see Source) < code > data.frame< / code > will have three rows (S/I/R) and a column for each variable with class < code > "rsi"< / code > .< / p >
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< h2 class = "hasAnchor" id = "read-more-on-our-website-" > < a class = "anchor" href = "#read-more-on-our-website-" > < / a > Read more on our website!< / h2 >
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< p > On our website < a href = 'https://msberends.gitlab.io/AMR' > https://msberends.gitlab.io/AMR< / a > you can find < a href = 'https://msberends.gitlab.io/AMR/articles/AMR.html' > a comprehensive tutorial< / a > about how to conduct AMR analysis, the < a href = 'https://msberends.gitlab.io/AMR/reference' > complete documentation of all functions< / a > (which reads a lot easier than here in R) and < a href = 'https://msberends.gitlab.io/AMR/articles/WHONET.html' > an example analysis using WHONET data< / a > .< / p >
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< h2 class = "hasAnchor" id = "see-also" > < a class = "anchor" href = "#see-also" > < / a > See also< / h2 >
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< div class = 'dont-index' > < p > < code > < a href = 'portion.html' > portion< / a > _*< / code > to calculate microbial resistance and susceptibility.< / p > < / div >
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< h2 class = "hasAnchor" id = "examples" > < a class = "anchor" href = "#examples" > < / a > Examples< / h2 >
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< pre class = "examples" > < span class = 'co' > # NOT RUN {< / span >
< span class = 'co' > # septic_patients is a data set available in the AMR package. It is true, genuine data.< / span >
?< span class = 'no' > septic_patients< / span >
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< span class = 'co' > # Count resistant isolates< / span >
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< span class = 'fu' > count_R< / span > (< span class = 'no' > septic_patients< / span > $< span class = 'no' > amox< / span > )
< span class = 'fu' > count_IR< / span > (< span class = 'no' > septic_patients< / span > $< span class = 'no' > amox< / span > )
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< span class = 'co' > # Or susceptible isolates< / span >
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< span class = 'fu' > count_S< / span > (< span class = 'no' > septic_patients< / span > $< span class = 'no' > amox< / span > )
< span class = 'fu' > count_SI< / span > (< span class = 'no' > septic_patients< / span > $< span class = 'no' > amox< / span > )
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< span class = 'co' > # Count all available isolates< / span >
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< span class = 'fu' > count_all< / span > (< span class = 'no' > septic_patients< / span > $< span class = 'no' > amox< / span > )
< span class = 'fu' > n_rsi< / span > (< span class = 'no' > septic_patients< / span > $< span class = 'no' > amox< / span > )
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< span class = 'co' > # Since n_rsi counts available isolates, you can< / span >
< span class = 'co' > # calculate back to count e.g. non-susceptible isolates.< / span >
< span class = 'co' > # This results in the same:< / span >
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< span class = 'fu' > count_IR< / span > (< span class = 'no' > septic_patients< / span > $< span class = 'no' > amox< / span > )
< span class = 'fu' > < a href = 'portion.html' > portion_IR< / a > < / span > (< span class = 'no' > septic_patients< / span > $< span class = 'no' > amox< / span > ) * < span class = 'fu' > n_rsi< / span > (< span class = 'no' > septic_patients< / span > $< span class = 'no' > amox< / span > )
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< span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/base/topics/library' > library< / a > < / span > (< span class = 'no' > dplyr< / span > )
< span class = 'no' > septic_patients< / span > < span class = 'kw' > %> %< / span >
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< span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/group_by.html' > group_by< / a > < / span > (< span class = 'no' > hospital_id< / span > ) < span class = 'kw' > %> %< / span >
< span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/summarise.html' > summarise< / a > < / span > (< span class = 'kw' > R< / span > < span class = 'kw' > =< / span > < span class = 'fu' > count_R< / span > (< span class = 'no' > cipr< / span > ),
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< span class = 'kw' > I< / span > < span class = 'kw' > =< / span > < span class = 'fu' > count_I< / span > (< span class = 'no' > cipr< / span > ),
< span class = 'kw' > S< / span > < span class = 'kw' > =< / span > < span class = 'fu' > count_S< / span > (< span class = 'no' > cipr< / span > ),
< span class = 'kw' > n1< / span > < span class = 'kw' > =< / span > < span class = 'fu' > count_all< / span > (< span class = 'no' > cipr< / span > ), < span class = 'co' > # the actual total; sum of all three< / span >
< span class = 'kw' > n2< / span > < span class = 'kw' > =< / span > < span class = 'fu' > n_rsi< / span > (< span class = 'no' > cipr< / span > ), < span class = 'co' > # same - analogous to n_distinct< / span >
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< span class = 'kw' > total< / span > < span class = 'kw' > =< / span > < span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/n.html' > n< / a > < / span > ()) < span class = 'co' > # NOT the number of tested isolates!< / span >
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< span class = 'co' > # Count co-resistance between amoxicillin/clav acid and gentamicin,< / span >
< span class = 'co' > # so we can see that combination therapy does a lot more than mono therapy.< / span >
< span class = 'co' > # Please mind that `portion_S` calculates percentages right away instead.< / span >
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< span class = 'fu' > count_S< / span > (< span class = 'no' > septic_patients< / span > $< span class = 'no' > amcl< / span > ) < span class = 'co' > # S = 1057 (67.1%)< / span >
< span class = 'fu' > count_all< / span > (< span class = 'no' > septic_patients< / span > $< span class = 'no' > amcl< / span > ) < span class = 'co' > # n = 1576< / span >
< span class = 'fu' > count_S< / span > (< span class = 'no' > septic_patients< / span > $< span class = 'no' > gent< / span > ) < span class = 'co' > # S = 1372 (74.0%)< / span >
< span class = 'fu' > count_all< / span > (< span class = 'no' > septic_patients< / span > $< span class = 'no' > gent< / span > ) < span class = 'co' > # n = 1855< / span >
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< span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/base/topics/with' > with< / a > < / span > (< span class = 'no' > septic_patients< / span > ,
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< span class = 'fu' > count_S< / span > (< span class = 'no' > amcl< / span > , < span class = 'no' > gent< / span > )) < span class = 'co' > # S = 1396 (92.0%)< / span >
< span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/base/topics/with' > with< / a > < / span > (< span class = 'no' > septic_patients< / span > , < span class = 'co' > # n = 1517< / span >
< span class = 'fu' > n_rsi< / span > (< span class = 'no' > amcl< / span > , < span class = 'no' > gent< / span > ))
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< span class = 'co' > # Get portions S/I/R immediately of all rsi columns< / span >
< span class = 'no' > septic_patients< / span > < span class = 'kw' > %> %< / span >
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< span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/select.html' > select< / a > < / span > (< span class = 'no' > amox< / span > , < span class = 'no' > cipr< / span > ) < span class = 'kw' > %> %< / span >
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< span class = 'fu' > count_df< / span > (< span class = 'kw' > translate< / span > < span class = 'kw' > =< / span > < span class = 'fl' > FALSE< / span > )
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< span class = 'co' > # It also supports grouping variables< / span >
< span class = 'no' > septic_patients< / span > < span class = 'kw' > %> %< / span >
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< span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/select.html' > select< / a > < / span > (< span class = 'no' > hospital_id< / span > , < span class = 'no' > amox< / span > , < span class = 'no' > cipr< / span > ) < span class = 'kw' > %> %< / span >
< span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/group_by.html' > group_by< / a > < / span > (< span class = 'no' > hospital_id< / span > ) < span class = 'kw' > %> %< / span >
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< span class = 'fu' > count_df< / span > (< span class = 'kw' > translate< / span > < span class = 'kw' > =< / span > < span class = 'fl' > FALSE< / span > )
< span class = 'co' > # }< / span > < / pre >
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< p > Developed by < a href = 'https://www.rug.nl/staff/m.s.berends/' > Matthijs S. Berends< / a > , < a href = 'https://www.rug.nl/staff/c.f.luz/' > Christian F. Luz< / a > , < a href = 'https://www.rug.nl/staff/c.glasner/' > Corinna Glasner< / a > , < a href = 'https://www.rug.nl/staff/a.w.friedrich/' > Alex W. Friedrich< / a > , < a href = 'https://www.rug.nl/staff/b.sinha/' > Bhanu N. M. Sinha< / a > .< / p >
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