R/nbpmatching-package.R

In couthcommander/nbpMatching: Functions for Optimal Non-Bipartite Matching

#'Nonbipartite Matching
#'
#'This package will take an input distance matrix and generate the set of
#'pairwise matches that minimizes the sum of distances between the pairs by
#'running nonbimatch.
#'
#'The most current documentation is available at
#'\url{https://biostat.app.vumc.org/wiki/Main/MatchedRandomization}.
#'
#'
#'@name nbpMatching-package
#'@aliases nbpMatching-package nbpMatching
#'@docType package
#'@author Bo Lu, Robert Greevy, Cole Beck
#'
#'Maintainer: Cole Beck \email{cole.beck@@vumc.org}
#'@references Lu B, Greevy R, Xu X, Beck C. Optimal Nonbipartite Matching and
#'its Statistical Applications. The American Statistician. Vol. 65, no. 1. :
#'21-30. 2011.
#'
#'Greevy RA Jr, Grijalva CG, Roumie CL, Beck C, Hung AM, Murff HJ, Liu X,
#'Griffin MR. Reweighted Mahalanobis distance matching for cluster-randomized
#'trials with missing data. Pharmacoepidemiol Drug Saf. 2012 May;21 Suppl
#'2:148-54. doi: 10.1002/pds.3260.
#'@keywords package cluster array
#'@import methods
#'@import stats
#'@importFrom Hmisc transcan hdquantile
#'@importFrom MASS ginv
#'@importFrom utils read.csv
#'@useDynLib nbpMatching, .registration = TRUE
#'@examples
#'
#'# create a covariate matrix
#'df <- data.frame(id=LETTERS[1:25], val1=rnorm(25), val2=rnorm(25))
#'# create distances
#'df.dist <- gendistance(df, idcol=1)
#'# create distancematrix object
#'df.mdm <- distancematrix(df.dist)
#'# create matches
#'df.match <- nonbimatch(df.mdm)
#'# review quality of matches
#'df.qom <- qom(df.dist$cov, df.match$matches)
#'
#'# some helper functions are available
#'# runner -- start with the covariate, run through the entire process
#'df.1 <- runner(df, idcol=1)
#'# full.qom -- start with the covariate, generate a full quality of match report
#'df.2 <- full.qom(df)
#'
#'\dontrun{
#'try a large matrix
#'nonbimatch(distancematrix(as.matrix(dist(sample(1:10^8, 5000, replace=TRUE)))))
#'}
#'
"_PACKAGE"

#'Internal nbpMatching objects.
#'
#'Internal nbpMatching objects.
#'
#'This function should not be called by the user.
#'
#'@name nbpMatching-internal
#'@aliases .requireCachedGenerics initialize,distancematrix-method
#'[<-,distancematrix,ANY,ANY,ANY-method [<-,distancematrix-method
#'[[<-,distancematrix,ANY,ANY,ANY-method [[<-,distancematrix-method
#'runner runner,data.frame-method full.qom full.qom,data.frame-method
#'show,nonbimatch-method
#'@exportMethod runner
#'@exportMethod full.qom
#'@keywords internal
#'
NULL

# .onAttach <- function(libname, pkgname) {
#     packageStartupMessage("Notice:
# Formerly the gendistance() function scaled the Mahalanobis distances into large
# integers, as required by the nonbimatch() function. Starting in version 1.5.0,
# gendistance() will return unscaled distances. This facilitates comparison to an
# appropriate F distribution for multivariate normal data. Any required scaling
# will happen invisibly within nonbimatch(). This notice will be removed in a
# future version of nbpMatching.")
# }