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update MIC comparisons
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4
R/sir.R
4
R/sir.R
@ -29,7 +29,7 @@
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#' Translate MIC and Disk Diffusion to SIR, or Clean Existing SIR Data
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#'
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#' @description Clean up existing SIR values, or interpret minimum inhibitory concentration (MIC) values and disk diffusion diameters according to EUCAST or CLSI. [as.sir()] transforms the input to a new class [`sir`], which is an ordered [factor] with levels `S < I < R`.
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#' @description Clean up existing SIR values, or interpret minimum inhibitory concentration (MIC) values and disk diffusion diameters according to EUCAST or CLSI. [as.sir()] transforms the input to a new class [`sir`], which is an ordered [factor].
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#'
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#' Currently breakpoints are available:
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#' - For **clinical microbiology** from EUCAST `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST" & type == "human")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "EUCAST" & type == "human")$guideline)))` and CLSI `r min(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI" & type == "human")$guideline)))`-`r max(as.integer(gsub("[^0-9]", "", subset(AMR::clinical_breakpoints, guideline %like% "CLSI" & type == "human")$guideline)))`;
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@ -326,7 +326,7 @@ as.sir.default <- function(x, ...) {
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x.bak <- x
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x <- as.character(x) # this is needed to prevent the vctrs pkg from throwing an error
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if (inherits(x.bak, c("integer", "numeric", "double")) && all(x %in% c(1:3, NA))) {
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if (inherits(x.bak, c("numeric", "integer")) && all(x %in% c(1:3, NA))) {
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# support haven package for importing e.g., from SPSS - it adds the 'labels' attribute
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lbls <- attributes(x.bak)$labels
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if (!is.null(lbls) && all(c("S", "I", "R") %in% names(lbls)) && all(c(1:3) %in% lbls)) {
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