It creates a 'lab.qcdata' class object to perform the interlaboratory study. This object is used to plot ILS data and more.
Usage
lab.qcdata(
data,
var.index = 1,
replicate.index = 2,
material.index = 3,
laboratory.index = 4,
data.name = NULL
)Arguments
- data
Matrix or data-frame that contains the data, replicate index, type of material, and the laboratory.
- var.index
Scalar with the column number corresponding to the observed variable (the critical to quality variable). Alternatively, a string with the name of a quality variable can be provided.
- replicate.index
Scalar with the column number corresponding to the index each replicate.
- material.index
Scalar corresponding to the replicated number.
- laboratory.index
Scalar that defines the index number of each laboratory.
- data.name
String specifying the name of the variable which appears on the plots. If name is not provided, it is retrieved from the object.
Examples
library(ILS)
data(Glucose)
Glucose.qcdata <- lab.qcdata(Glucose)
str(Glucose.qcdata)
#> Classes ‘lab.qcdata’ and 'data.frame': 120 obs. of 4 variables:
#> $ x : num 41 41.5 41.4 41.2 42 ...
#> $ replicate : Factor w/ 3 levels "1","2","3": 1 2 3 1 2 3 1 2 3 1 ...
#> $ material : Factor w/ 5 levels "A","B","C","D",..: 1 1 1 1 1 1 1 1 1 1 ...
#> $ laboratory: Factor w/ 8 levels "Lab1","Lab2",..: 1 1 1 2 2 2 3 3 3 4 ...
#> - attr(*, "data.name")= chr "Glucose"
summary(Glucose.qcdata)
#> x replicate material laboratory
#> Min. : 39.02 1:40 A:24 Lab1 :15
#> 1st Qu.: 78.45 2:40 B:24 Lab2 :15
#> Median :135.03 3:40 C:24 Lab3 :15
#> Mean :149.09 D:24 Lab4 :15
#> 3rd Qu.:196.66 E:24 Lab5 :15
#> Max. :309.40 Lab6 :15
#> (Other):30