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