ILS (version 0.3)

lab.aov: Function to compute the AOV

Description

Function to compute the analysis of variance of ILS data, taking into account the laboratories and material factors.

Usage

lab.aov(x, ...)
# S3 method for default
lab.aov(
  x,
  var.index = 1,
  replicate.index = 2,
  material.index = 3,
  laboratory.index = 4,
  data.name = NULL,
  level = 0.95,
  plot = FALSE,
  pages = 0,
  ...
)
# S3 method for lab.qcdata
lab.aov(x, level = 0.95, plot = FALSE, pages = 0, ...)

Arguments

x

An object of class lab.qcdata (Univariate Quality Control Data).

...

Other arguments passed to or from methods.

var.index

A scalar with the column number corresponding to the observed variable (the critical to quality variable). Alternativelly can be a string with the name of the quality variable.

replicate.index

A scalar with the column number corresponding to the index each replicate.

material.index

A scalar corresponding to the replicated number.

laboratory.index

A scalar that defines the index number of each laboratory.

data.name

A string specifying the name of the variable which appears on the plots. If name is not provided, it is taken from the object given as data.

level

Requested confidence level (0.95 by default).

plot

If TRUE, confidence intervals are plot.

pages

By default 0, it indicates the number of pages over which to spread the output. For example, if pages=1, all terms will be plotted on one page with the layout performed automatically. If pages=0, one plot will be displayed by each tested material.

References

WHothorn T., Bretz, F., and Westfall, P. (2008), Simultaneous inference in general parametric models. Biometrical Journal, 50(3):346-363.

Heyden, Y., Smeyers-Verbeke, J. (2007), Set-up and evaluation of interlaboratory studies. J. Chromatogr. A, 1158:158-167.

Examples

if (FALSE) {
library(ILS)
data(Glucose)
Glucose.qcdata <- lab.qcdata(Glucose)
str(Glucose.qcdata)
lab.aov(Glucose.qcdata,level = 0.95, plot = TRUE, pages = 1)
}