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@@ -13,49 +13,64 @@ from the `dplyr` package and also support grouped variables, see
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## Usage
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``` r
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resistance(..., minimum = 30, as_percent = FALSE,
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only_all_tested = FALSE, guideline = getOption("AMR_guideline",
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"EUCAST"))
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resistance(
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...,
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minimum = 30,
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as_percent = FALSE,
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only_all_tested = FALSE,
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guideline = getOption("AMR_guideline", "EUCAST")
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)
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susceptibility(..., minimum = 30, as_percent = FALSE,
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only_all_tested = FALSE, guideline = getOption("AMR_guideline",
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"EUCAST"))
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susceptibility(
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...,
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minimum = 30,
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as_percent = FALSE,
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only_all_tested = FALSE,
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guideline = getOption("AMR_guideline", "EUCAST")
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)
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sir_confidence_interval(..., ab_result = "R", minimum = 30,
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as_percent = FALSE, only_all_tested = FALSE, confidence_level = 0.95,
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side = "both", collapse = FALSE)
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sir_confidence_interval(
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...,
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ab_result = "R",
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minimum = 30,
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as_percent = FALSE,
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only_all_tested = FALSE,
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confidence_level = 0.95,
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side = "both",
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collapse = FALSE
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)
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proportion_R(..., minimum = 30, as_percent = FALSE,
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only_all_tested = FALSE)
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proportion_R(..., minimum = 30, as_percent = FALSE, only_all_tested = FALSE)
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proportion_IR(..., minimum = 30, as_percent = FALSE,
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only_all_tested = FALSE)
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proportion_IR(..., minimum = 30, as_percent = FALSE, only_all_tested = FALSE)
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proportion_I(..., minimum = 30, as_percent = FALSE,
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only_all_tested = FALSE)
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proportion_I(..., minimum = 30, as_percent = FALSE, only_all_tested = FALSE)
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proportion_SI(..., minimum = 30, as_percent = FALSE,
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only_all_tested = FALSE)
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proportion_SI(..., minimum = 30, as_percent = FALSE, only_all_tested = FALSE)
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proportion_S(..., minimum = 30, as_percent = FALSE,
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only_all_tested = FALSE)
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proportion_S(..., minimum = 30, as_percent = FALSE, only_all_tested = FALSE)
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proportion_df(data, translate_ab = "name", language = get_AMR_locale(),
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minimum = 30, as_percent = FALSE, combine_SI = TRUE,
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confidence_level = 0.95)
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proportion_df(
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data,
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translate_ab = "name",
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language = get_AMR_locale(),
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minimum = 30,
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as_percent = FALSE,
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combine_SI = TRUE,
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confidence_level = 0.95
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)
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sir_df(data, translate_ab = "name", language = get_AMR_locale(),
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minimum = 30, as_percent = FALSE, combine_SI = TRUE,
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confidence_level = 0.95)
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sir_df(
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data,
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translate_ab = "name",
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language = get_AMR_locale(),
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minimum = 30,
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as_percent = FALSE,
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combine_SI = TRUE,
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confidence_level = 0.95
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)
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```
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## Source
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**M39 Analysis and Presentation of Cumulative Antimicrobial
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Susceptibility Test Data, 5th Edition**, 2022, *Clinical and Laboratory
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Standards Institute (CLSI)*.
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<https://clsi.org/standards/products/microbiology/documents/m39/>.
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## Arguments
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- ...:
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@@ -262,6 +277,13 @@ This AMR package follows insight; use `susceptibility()` (equal to
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to [`count_SI()`](https://amr-for-r.org/reference/count.md)) to count
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susceptible isolates.
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## References
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**M39 Analysis and Presentation of Cumulative Antimicrobial
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Susceptibility Test Data, 5th Edition**, 2022, *Clinical and Laboratory
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Standards Institute (CLSI)*.
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<https://clsi.org/standards/products/microbiology/documents/m39/>.
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## See also
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[`count()`](https://amr-for-r.org/reference/count.md) to count resistant
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