View source: R/matrix_effect.R
matrix_effect | R Documentation |
Calculate the matrix effect by comparing the slope of a solvent-based calibration curve with one or more matrix-matched calibration. The matrix effect is expressed as signal suppression/enhancement ratio.
matrix_effect(object, ...) ## S3 method for class 'calibration' matrix_effect(object, ...)
object |
an object of class ' |
... |
additional objects of the same type obtained from matrix-matched calibration data. |
Matrix effects or signal suppression/enhancement ratios should be evaluated during analytical method development to avoid over- or underestimation of sample concentrations. In addition, signal suppression/enhancement ratios may help to justify the validity of a regular solvent calibration as opposed to matrix-matched calibrations. This may be the case if matrix effects or signal suppression/enhancement ratios are close to measurement repeatability.
The magnitude of a matrix effect is estimated by subtracting the slope of a matrix-matched calibration from that of the solvent-based calibration. The difference is divided by the slope of the solvent-based calibration.
Julius Albert, Zacharias Steinmetz
Other calibration:
calibration()
,
din32645
,
icp
,
neitzel2003
,
weight_select()
data(din32645) din <- calibration(Area ~ Conc, data = din32645) m32645 <- din32645 m32645$Area <- din32645$Area * 1.5 matrix <- calibration(Area ~ Conc, data = m32645) matrix_effect(din, matrix)
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