lab.aov | R Documentation |
Function to compute the analysis of variance of ILS data, taking into account the laboratories and material factors.
lab.aov(x, ...) ## Default S3 method: 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 class 'lab.qcdata' lab.aov(x, level = 0.95, plot = FALSE, pages = 0, ...)
x |
An object of class |
... |
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. |
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.
## Not run: library(ILS) data(Glucose) Glucose.qcdata <- lab.qcdata(Glucose) str(Glucose.qcdata) lab.aov(Glucose.qcdata,level = 0.95, plot = TRUE, pages = 1) ## End(Not run)
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