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(v1.4.0.9026) docu update
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#'
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#' Determine first (weighted) isolates of all microorganisms of every patient per episode and (if needed) per specimen type. To determine patient episodes not necessarily based on microorganisms, use [is_new_episode()] that also supports grouping with the `dplyr` package.
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#' @inheritSection lifecycle Stable lifecycle
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#' @param x,.data a [data.frame] containing isolates.
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#' @param x a [data.frame] containing isolates.
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#' @param col_date column name of the result date (or date that is was received on the lab), defaults to the first column with a date class
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#' @param col_patient_id column name of the unique IDs of the patients, defaults to the first column that starts with 'patient' or 'patid' (case insensitive)
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#' @param col_mo column name of the IDs of the microorganisms (see [as.mo()]), defaults to the first column of class [`mo`]. Values will be coerced using [as.mo()].
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#' @param points_threshold points until the comparison of key antibiotics will lead to inclusion of an isolate when `type = "points"`, see Details
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#' @param info print progress
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#' @param include_unknown logical to determine whether 'unknown' microorganisms should be included too, i.e. microbial code `"UNKNOWN"`, which defaults to `FALSE`. For WHONET users, this means that all records with organism code `"con"` (*contamination*) will be excluded at default. Isolates with a microbial ID of `NA` will always be excluded as first isolate.
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#' @param ... parameters passed on to the [first_isolate()] function
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#' @param ... parameters passed on to [first_isolate()] when using [filter_first_isolate()], or parameters passed on to [key_antibiotics()] when using [filter_first_weighted_isolate()]
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#' @details The [first_isolate()] function is a wrapper around the [is_new_episode()] function, but more efficient for data sets containing microorganism codes or names.
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#'
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#' All isolates with a microbial ID of `NA` will be excluded as first isolate.
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