P281424/AMR
1
0
Fork 0
mirror of https://github.com/msberends/AMR.git synced 2025-07-08 18:41:58 +02:00
Code Releases Activity

(v0.8.0.9037) complete documentation rewrite

Browse Source
This commit is contained in:
dr. M.S. (Matthijs) Berends
2019-11-28 23:00:37 +01:00
parent c5f00f4a9f
commit 9feef53bde
37 changed files with 59 additions and 53 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
man/AMR.Rd
View File

@ -36,7 +36,7 @@ On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://
For suggestions, comments or questions, please contact us at:
Matthijs S. Berends \cr
m.s.berends \link{at} umcg \link{dot} nl \cr
m.s.berends at umcg dot nl \cr
Department of Medical Microbiology, University of Groningen \cr
University Medical Center Groningen \cr
Post Office Box 30001 \cr

2
man/as.mic.Rd
View File

@ -2,7 +2,7 @@
% Please edit documentation in R/mic.R
\name{as.mic}
\alias{as.mic}
\alias{MIC}
\alias{mic}
\alias{is.mic}
\title{Class 'mic'}
\usage{

2
man/as.rsi.Rd
View File

@ -2,7 +2,7 @@
% Please edit documentation in R/rsi.R
\name{as.rsi}
\alias{as.rsi}
\alias{RSI}
\alias{rsi}
\alias{as.rsi.mic}
\alias{as.rsi.disk}
\alias{as.rsi.data.frame}

2
man/first_isolate.Rd
View File

@ -94,7 +94,7 @@ Determine first (weighted) isolates of all microorganisms of every patient per e
}
\details{
\strong{WHY THIS IS SO IMPORTANT} \cr
To conduct an analysis of antimicrobial resistance, you should only include the first isolate of every patient per episode [\link{1}](https://www.ncbi.nlm.nih.gov/pubmed/17304462). If you would not do this, you could easily get an overestimate or underestimate of the resistance of an antibiotic. Imagine that a patient was admitted with an MRSA and that it was found in 5 different blood cultures the following week. The resistance percentage of oxacillin of all \emph{S. aureus} isolates would be overestimated, because you included this MRSA more than once. It would be \href{https://en.wikipedia.org/wiki/Selection_bias}{selection bias}.
To conduct an analysis of antimicrobial resistance, you should only include the first isolate of every patient per episode \href{https://www.ncbi.nlm.nih.gov/pubmed/17304462}{(ref)}. If you would not do this, you could easily get an overestimate or underestimate of the resistance of an antibiotic. Imagine that a patient was admitted with an MRSA and that it was found in 5 different blood cultures the following week. The resistance percentage of oxacillin of all \emph{S. aureus} isolates would be overestimated, because you included this MRSA more than once. It would be \href{https://en.wikipedia.org/wiki/Selection_bias}{selection bias}.
All isolates with a microbial ID of \code{NA} will be excluded as first isolate.

6
man/g.test.Rd
View File

@ -49,7 +49,7 @@ A list with class \code{"htest"} containing the following
section 2.4.5 for the case where \code{x} is a matrix, \code{n * p * (1 - p)} otherwise).}
}
\description{
\code{\link[=g.test]{g.test()}} performs chi-squared contingency table tests and goodness-of-fit tests, just like \code{\link[=chisq.test]{chisq.test()}} but is more reliable \link{1}. A \emph{G}-test can be used to see whether the number of observations in each category fits a theoretical expectation (called a \strong{\emph{G}-test of goodness-of-fit}), or to see whether the proportions of one variable are different for different values of the other variable (called a \strong{\emph{G}-test of independence}).
\code{\link[=g.test]{g.test()}} performs chi-squared contingency table tests and goodness-of-fit tests, just like \code{\link[=chisq.test]{chisq.test()}} but is more reliable (1). A \emph{G}-test can be used to see whether the number of observations in each category fits a theoretical expectation (called a \strong{\emph{G}-test of goodness-of-fit}), or to see whether the proportions of one variable are different for different values of the other variable (called a \strong{\emph{G}-test of independence}).
}
\details{
If \code{x} is a matrix with one row or column, or if \code{x} is a vector and \code{y} is not given, then a \emph{goodness-of-fit test} is performed (\code{x} is treated as a one-dimensional contingency table). The entries of \code{x} must be non-negative integers. In this case, the hypothesis tested is whether the population probabilities equal those in \code{p}, or are all equal if \code{p} is not given.
@ -137,7 +137,9 @@ g.test(x)
}
\references{
\link{1} McDonald, J.H. 2014. \strong{Handbook of Biological Statistics (3rd ed.)}. Sparky House Publishing, Baltimore, Maryland. \url{http://www.biostathandbook.com/gtestgof.html}.
\enumerate{
\item McDonald, J.H. 2014. \strong{Handbook of Biological Statistics (3rd ed.)}. Sparky House Publishing, Baltimore, Maryland. \url{http://www.biostathandbook.com/gtestgof.html}.
}
}
\seealso{
\code{\link[=chisq.test]{chisq.test()}}

2
man/join.Rd
View File

@ -36,7 +36,7 @@ anti_join_microorganisms(x, by = NULL, ...)
Join the data set \link{microorganisms} easily to an existing table or character vector.
}
\details{
\strong{Note:} As opposed to the \code{\link[dplyr:join]{dplyr::join()}} functions of \code{dplyr}, \code{\link{characters}} vectors are supported and at default existing columns will get a suffix \code{"2"} and the newly joined columns will not get a suffix. See \code{\link[dplyr:join]{dplyr::join()}} for more information.
\strong{Note:} As opposed to the \code{\link[dplyr:join]{dplyr::join()}} functions of \code{dplyr}, \code{\link{character}} vectors are supported and at default existing columns will get a suffix \code{"2"} and the newly joined columns will not get a suffix. See \code{\link[dplyr:join]{dplyr::join()}} for more information.
}
\section{Read more on our website!}{

2
man/kurtosis.Rd
View File

@ -16,7 +16,7 @@ kurtosis(x, na.rm = FALSE)
\method{kurtosis}{data.frame}(x, na.rm = FALSE)
}
\arguments{
\item{x}{a vector of values, a \code{\link{matrix}} or a \code{\link{data frame}}}
\item{x}{a vector of values, a \code{\link{matrix}} or a \code{\link{data.frame}}}
\item{na.rm}{a logical value indicating whether \code{NA} values should be stripped before the computation proceeds.}
}

2
man/mdro.Rd
View File

@ -85,7 +85,7 @@ The international guideline for multi-drug resistant tuberculosis - World Health
\item \code{guideline = "MRGN"}\cr
The German national guideline - Mueller et al. (2015) Antimicrobial Resistance and Infection Control 4:7. DOI: 10.1186/s13756-015-0047-6
\item \code{guideline = "BRMO"}\cr
The Dutch national guideline - Rijksinstituut voor Volksgezondheid en Milieu "WIP-richtlijn BRMO (Bijzonder Resistente Micro-Organismen) \link{ZKH}" (\href{https://www.rivm.nl/Documenten_en_publicaties/Professioneel_Praktisch/Richtlijnen/Infectieziekten/WIP_Richtlijnen/WIP_Richtlijnen/Ziekenhuizen/WIP_richtlijn_BRMO_Bijzonder_Resistente_Micro_Organismen_ZKH}{link})
The Dutch national guideline - Rijksinstituut voor Volksgezondheid en Milieu "WIP-richtlijn BRMO (Bijzonder Resistente Micro-Organismen) (ZKH)" (\href{https://www.rivm.nl/Documenten_en_publicaties/Professioneel_Praktisch/Richtlijnen/Infectieziekten/WIP_Richtlijnen/WIP_Richtlijnen/Ziekenhuizen/WIP_richtlijn_BRMO_Bijzonder_Resistente_Micro_Organismen_ZKH}{link})
}
Please suggest your own (country-specific) guidelines by letting us know: \url{https://gitlab.com/msberends/AMR/issues/new}.

2
man/microorganisms.Rd
View File

@ -31,7 +31,7 @@ A data set containing the microbial taxonomy of six kingdoms from the Catalogue
Manually added were:
\itemize{
\item 11 entries of \emph{Streptococcus} (beta-haemolytic: groups A, B, C, D, F, G, H, K and unspecified; other: viridans, milleri)
\item 2 entries of \emph{Staphylococcus} (coagulase-negative \link{CoNS} and coagulase-positive \link{CoPS})
\item 2 entries of \emph{Staphylococcus} (coagulase-negative (CoNS) and coagulase-positive (CoPS))
\item 3 entries of \emph{Trichomonas} (\emph{Trichomonas vaginalis}, and its family and genus)
\item 1 entry of \emph{Blastocystis} (\emph{Blastocystis hominis}), although it officially does not exist (Noel \emph{et al.} 2005, PMID 15634993)
\item 5 other 'undefined' entries (unknown, unknown Gram negatives, unknown Gram positives, unknown yeast and unknown fungus)