This transforms a vector to a new class mic
, which is an ordered factor
with valid MIC values as levels. Invalid MIC values will be translated as NA
with a warning.
as.mic(x, na.rm = FALSE) is.mic(x)
x | vector |
---|---|
na.rm | a logical indicating whether missing values should be removed |
Ordered factor
with new class mic
To interpret MIC values as RSI values, use as.rsi()
on MIC values. It supports guidelines from EUCAST and CLSI.
The lifecycle of this function is stable. In a stable function, we are largely happy with the unlying code, and major changes are unlikely. This means that the unlying code will generally evolve by adding new arguments; we will avoid removing arguments or changing the meaning of existing arguments.
If the unlying code needs breaking changes, they will occur gradually. To begin with, the function or argument will be deprecated; it will continue to work but will emit an message informing you of the change. Next, typically after at least one newly released version on CRAN, the message will be transformed to an error.
On our website https://msberends.gitlab.io/AMR you can find a comprehensive tutorial about how to conduct AMR analysis, the complete documentation of all functions (which reads a lot easier than here in R) and an example analysis using WHONET data.
mic_data <- as.mic(c(">=32", "1.0", "1", "1.00", 8, "<=0.128", "8", "16", "16")) is.mic(mic_data) # this can also coerce combined MIC/RSI values: as.mic("<=0.002; S") # will return <=0.002 # interpret MIC values as.rsi(x = as.mic(2), mo = as.mo("S. pneumoniae"), ab = "AMX", guideline = "EUCAST") as.rsi(x = as.mic(4), mo = as.mo("S. pneumoniae"), ab = "AMX", guideline = "EUCAST") plot(mic_data) barplot(mic_data) freq(mic_data)