Defines a calibration object for the calculation of concentrations
from measurement signals including estimations for the limit of detection
(LOD) and limit of quantification (LOQ) in accordance with DIN 32645 (2008).
The LOD is defined as the lowest quantity of a substance that can be
distinguished from the absence of that substance (blank value) within a
given confidence level (alpha). The LOQ is defined as the lowest quantity of
a substance that can be quantified/distinguished from another sample given
with respect to a defined confidence level (k).
calibration(
formula,
data = NULL,
blanks = NULL,
weights = NULL,
model = "lm",
check_assumptions = TRUE,
...
)# S3 method for calibration
print(x, ...)
# S3 method for calibration
summary(object, ...)
# S3 method for calibration
plot(x, interval = "conf", level = 0.95, ...)
lod(object, ...)
# S3 method for calibration
lod(object, blanks = NULL, alpha = 0.01, level = 0.05, ...)
loq(object, ...)
# S3 method for calibration
loq(
object,
blanks = NULL,
alpha = 0.01,
k = 3,
level = 0.05,
maxiter = 10,
...
)
calibration returns an object of class
'calibration'. print() calls the function parameters together with the
respective LOD and LOQ. plot() plots the respective calibration curve
together with the measurement values. summary() may be used to retrieve
the summary of the underlying model.
model formula providing the recorded signal intensities with
respect to the nominal analyte concentrations in the form of
signal ~ concentration or signal ~ concentration - 1; model
formulas are currently restricted to those forms, however, the possibility
to use log or sqrt transformed data will be implemented in the
future.
an optional data frame containing the variables in the model.
a vector of numeric blank values overriding those automatically retrieved from calibration data.
an optional character string containing one or more model
variables, for example, in the form of "1/concentration^0.5" or
"1/signal" which is internally converted to a numeric vector and
passed to the fitting process of the selected model.
model class to be used for fitting; currently,
lm() and rlm() are supported.
automatically check for normality and
homoscedasticity of model residuals using shapiro.test()
and bptest(), respectively; only executed if
weights == NULL.
further arguments passed to the submethod, namely the
respective model environment such as lm(), plot(), or
print().
an object of class 'calibration' with a model formula
as shown above.
Type of interval calculation (can be abbreviated); see
predict() for details.
tolerance/confidence level; see predict()
and confint() for details.
error tolerance for the detection limit (critical value).
relative uncertainty for the limit of quantification
(1/beta).
a positive integer specifying the maximum number of iterations to calculate the LOQ.
Zacharias Steinmetz
If the data supplied to calibration contain more than one blank
value, namely measurements with a nominal concentration of or close to zero,
the LOD and LOQ are calculated from the deviation of the blank samples. This
method is called "blank method" according to DIN 32645 (2008) and supposed
to be more accurate than the so-called "calibration method" which will be
used for the estimation of LOD and LOQ when data does not contain zero
concentration measurements.
Almeida, A. M. D., Castel-Branco, M. M., & Falcao, A. C. (2002). Linear regression for calibration lines revisited: weighting schemes for bioanalytical methods. Journal of Chromatography B, 774(2), 215-222. tools:::Rd_expr_doi("10.1016/S1570-0232(02)00244-1").
Currie, L.A. (1999). Nomenclature in evaluation of analytical methods including detection and quantification capabilities: (IUPAC Recommendations 1995). Analytica Chimica Acta 391, 105-126.
DIN 32645 (2008). Chemical analysis - Decision limit, detection limit and determination limit under repeatability conditions - Terms, methods, evaluation. Technical standard. Deutsches Institut für Normung, Berlin.
Massart, D.L., Vandeginste, B.G., Buydens, L.M.C., Lewi, P.J., & Smeyers-Verbeke, J. (1997). Handbook of chemometrics and qualimetrics: Part A. Elsevier Science Inc.
Other calibration:
din32645,
icp,
matrix_effect(),
neitzel2003,
weight_select()
data(din32645)
din <- calibration(Area ~ Conc, data = din32645)
din
plot(din)
summary(din)
lod(din)
loq(din)
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