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< h1 > Class 'rsi'< / h1 >
< div class = "hidden name" > < code > as.rsi.Rd< / code > < / div >
< / div >
< div class = "ref-description" >
< p > This transforms a vector to a new class < code > rsi< / code > , which is an ordered factor with levels < code > S < I < R< / code > . Invalid antimicrobial interpretations will be translated as < code > NA< / code > with a warning.< / p >
< / div >
< pre class = "usage" > < span class = 'fu' > as.rsi< / span > (< span class = 'no' > x< / span > )
< span class = 'fu' > is.rsi< / span > (< span class = 'no' > x< / span > )
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< span class = 'fu' > is.rsi.eligible< / span > (< span class = 'no' > x< / span > , < span class = 'kw' > threshold< / span > < span class = 'kw' > =< / span > < span class = 'fl' > 0.05< / span > )< / pre >
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< 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 > x< / th >
< td > < p > vector< / p > < / td >
< / tr >
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< tr >
< th > threshold< / th >
< td > < p > maximum fraction of < code > x< / code > that is allowed to fail transformation, see Examples< / p > < / td >
< / tr >
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< / table >
< h2 class = "hasAnchor" id = "value" > < a class = "anchor" href = "#value" > < / a > Value< / h2 >
< p > Ordered factor with new class < code > rsi< / code > < / p >
< h2 class = "hasAnchor" id = "details" > < a class = "anchor" href = "#details" > < / a > Details< / h2 >
< p > The function < code > is.rsi.eligible< / code > returns < code > TRUE< / code > when a columns contains only valid antimicrobial interpretations (S and/or I and/or R), and < code > FALSE< / code > otherwise.< / 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 >
< p > < img src = 'figures/logo.png' height = 40px style = margin-bottom:5px / > < br / >
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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 = 'as.mic.html' > as.mic< / a > < / code > < / 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 = 'no' > rsi_data< / span > < span class = 'kw' > < -< / span > < span class = 'fu' > as.rsi< / span > (< span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/base/topics/c' > c< / a > < / span > (< span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/base/topics/rep' > rep< / a > < / span > (< span class = 'st' > "S"< / span > , < span class = 'fl' > 474< / span > ), < span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/base/topics/rep' > rep< / a > < / span > (< span class = 'st' > "I"< / span > , < span class = 'fl' > 36< / span > ), < span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/base/topics/rep' > rep< / a > < / span > (< span class = 'st' > "R"< / span > , < span class = 'fl' > 370< / span > )))
< span class = 'no' > rsi_data< / span > < span class = 'kw' > < -< / span > < span class = 'fu' > as.rsi< / span > (< span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/base/topics/c' > c< / a > < / span > (< span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/base/topics/rep' > rep< / a > < / span > (< span class = 'st' > "S"< / span > , < span class = 'fl' > 474< / span > ), < span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/base/topics/rep' > rep< / a > < / span > (< span class = 'st' > "I"< / span > , < span class = 'fl' > 36< / span > ), < span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/base/topics/rep' > rep< / a > < / span > (< span class = 'st' > "R"< / span > , < span class = 'fl' > 370< / span > ), < span class = 'st' > "A"< / span > , < span class = 'st' > "B"< / span > , < span class = 'st' > "C"< / span > ))
< span class = 'fu' > is.rsi< / span > (< span class = 'no' > rsi_data< / span > )
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< span class = 'co' > # this can also coerce combined MIC/RSI values:< / span >
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< span class = 'fu' > as.rsi< / span > (< span class = 'st' > "< = 0.002; S"< / span > ) < span class = 'co' > # will return S< / span >
< span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/graphics/topics/plot' > plot< / a > < / span > (< span class = 'no' > rsi_data< / span > ) < span class = 'co' > # for percentages< / span >
< span class = 'fu' > < a href = 'https://www.rdocumentation.org/packages/graphics/topics/barplot' > barplot< / a > < / span > (< span class = 'no' > rsi_data< / span > ) < span class = 'co' > # for frequencies< / span >
< span class = 'fu' > < a href = 'freq.html' > freq< / a > < / span > (< span class = 'no' > rsi_data< / span > ) < span class = 'co' > # frequency table with informative header< / span >
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< span class = 'co' > # using dplyr's mutate< / span >
< 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/summarise_all.html' > mutate_at< / a > < / span > (< span class = 'fu' > < a href = 'https://dplyr.tidyverse.org/reference/vars.html' > vars< / a > < / span > (< span class = 'no' > peni< / span > :< span class = 'no' > rifa< / span > ), < span class = 'no' > as.rsi< / span > )
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< span class = 'co' > # fastest way to transform all columns with already valid AB results to class `rsi`:< / 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/summarise_all.html' > mutate_if< / a > < / span > (< span class = 'no' > is.rsi.eligible< / span > ,
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< span class = 'no' > as.rsi< / span > )
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< span class = 'co' > # default threshold of `is.rsi.eligible` is 5%.< / span >
< span class = 'fu' > is.rsi.eligible< / span > (< span class = 'no' > WHONET< / span > $< span class = 'no' > `First name`< / span > ) < span class = 'co' > # fails, > 80% is invalid< / span >
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< span class = 'fu' > is.rsi.eligible< / span > (< span class = 'no' > WHONET< / span > $< span class = 'no' > `First name`< / span > , < span class = 'kw' > threshold< / span > < span class = 'kw' > =< / span > < span class = 'fl' > 0.9< / span > ) < span class = 'co' > # succeeds< / span >
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< span class = 'co' > # }< / span > < / pre >
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