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MethComp (version 1.30.0)

Meth: Create a Meth object representing a method comparison study

Description

Creates a dataframe with columns meth, item, (repl) and y.

Usage

Meth(
  data = NULL,
  meth = "meth",
  item = "item",
  repl = NULL,
  y = "y",
  print = !is.null(data),
  keep.vars = !is.null(data)
)

Value

The Meth function returns a Meth object which is a dataframe with columns meth, item, (repl) and y. summary.Meth returns a table classified by method and no. of replicate measurements, extended with columns of the total number of items, total number of observations and the range of the measurements.

Arguments

data

A data frame

meth

Vector of methods, numeric, character or factor. Can also be a number or character referring to a column in data.

item

Vector of items, numeric, character or factor. Can also be a number or character referring to a column in data.

repl

Vector of replicates, numeric, character or factor. Can also be a number or character referring to a column in data.

y

Vector of measurements. Can also be a character or numerical vector pointing to columns in data which contains the measurements by different methods or a dataframe with columns representing measurements by different methods. In this case the argument meth is ignored, and the names of the columns are taken as method names.

print

Logical: Should a summary result be printed?

keep.vars

Logical. Should the remaining variables from the dataframe data be transferred to the Meth object.

Details

In order to perform analyses of method comparisons it is convenient to have a dataframe with classifying factors, meth, item, and possibly repl and the response variable y. This function creates such a dataframe, and gives it a class, Meth, for which there is a number of methods: summary - tabulation, plot - plotting and a couple of analysis methods.

If there are replicates in the values of item it is assumed that those observations represent replicate measurements and different replicate numbers are given to those.

Examples

Run this code
data(fat)
# Different ways of selecting columns and generating replicate numbers
Sub1 <- Meth(fat,meth=2,item=1,repl=3,y=4,print=TRUE)
Sub2 <- Meth(fat,2,1,3,4,print=TRUE)
Sub3 <- Meth(fat,meth="Obs",item="Id",repl="Rep",y="Sub",print=TRUE)
summary( Sub3 )
plot( Sub3 )

# Use observation in different columns as methods
data( CardOutput )
head( CardOutput )
sv <- Meth( CardOutput, y=c("Svo2","Scvo2") )
# Note that replicates are generated if a non-unique item-id is used
sv <- Meth( CardOutput, y=c("Svo2","Scvo2"), item="Age" )
str( sv )
# A summary is not created if the the first argument (data=) is not used:
sv <- Meth( y=CardOutput[,c("Svo2","Scvo2")], item=CardOutput$VO2 )
summary(sv)

# Sample items
ssv <- sample.Meth( sv, how="item", N=8 )

# More than two methods
data( sbp )
plot( Meth( sbp ) )
# Creating non-unique replicate numbers per (meth,item) creates a warning:
data( hba1c )
hb1  <- with( hba1c,
              Meth( meth=dev, item=item, repl=d.ana-d.samp, y=y, print=TRUE ) )
hb2  <- with( subset(hba1c,type=="Cap"),
              Meth( meth=dev, item=item, repl=d.ana-d.samp, y=y, print=TRUE ) )

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