Design of experiments for the determination of the detection limit in chemical analysis (original) (raw)
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Once Again About Determination and Detection Limits
The papers takes stock of different methods for evaluating the detection (cmin) and determination (c lim) limits of components described in the literature and presents a comparative analysis of the results of such evaluations. It is shown that use of the data on the fluctuations of the blank experiment, in spite of their wide application for such evaluations, gives ambiguous estimates for cmin and clim. The most correct method for evaluating the specified parameters is the experimental determination of the actual analyte concentration (content) from the empirical concentration dependence of the relative standard deviation. In case when this estimation method cannot be used, it is recommended to evaluate clim by the lower boundary of the calibration graph. The article may be useful for inexperienced analysts experimenters in choosing a method for evalluating the results obtained.
Clarification of the limit of detection in chromatography
Chromatographia, 1984
Current problems with the limit of detection (LOD) concept in chromatography are reviewed. They include the confusion of the LOD with other separate, distinct concepts in trace analysis such as the minimum detectability (MD); the use of arbitrary, unjustified models for the calculation of the LOD; the use of concentration units instead of units of amount; and the failure to account for differences in chromatographic conditions when comparing LODs.
2007
When reporting or using results of quantitative analysis, it is important to understand the uncertainties associated with the reported values. Every method, no matter how good, has limitations that create some degree of measurement error, which can be manifested as inaccuracy, imprecision, or a combination of these. Relative measurement error tends to increase as analyte concentrations decrease, because analyte responses decrease in relation to background signals. At very low concentrations, analyte signals become difficult to distinguish from background signals, resulting in high rates of false positives (reporting a detection when no analyte is present) and false negatives (reporting no detection when the analyte is present).
Analytica Chimica Acta, 2004
The utility of analytical chemistry measurements in most applications is dependent on an assessment of measurement error. This paper demonstrates the use of a two-component error model in setting limits of detection and related concepts and introduces two goodness-of-fit statistics for assessing the appropriateness of the model for the data at hand. The model is applicable to analytical methods in which high concentrations are measured with approximately constant relative standard deviation. At low levels, the relative standard deviation cannot stay constant, since this implies vanishingly small absolute standard deviation. The two-component model has approximately constant standard deviation near zero concentration, and approximately constant relative standard deviation at high concentrations, a pattern that is frequently observed in practice. Here we discuss several important applications of the model to environmental monitoring and also introduce two goodness-of-fit statistics, to ascertain whether the data exhibit the error structure assumed by the model, as well as to look for problems with experimental design.
Estimation of the Tolerance Level of Interfering Substances in Instrumental Analytical Methods
Analytical Letters, 1995
A model to estimate the tolerance level of interfering substances for analytical procedures, applying the linear simple regression, is proposed. The confidence interval on the analytical signal for the selected concentration value to check the interference, is calculated using the calibration data set. The tolerance levels of molybdenum, aluminium and iron in the spectro fluorimetric determination of boron with Alizarin Red S by means of direct, synchronous and first-and second-derivative methods, are estimated. The adequate selection of an analyte concentration for the interferent test is discussed.
Computing detection limits in multicomponent spectroscopic analysis
TrAC Trends in Analytical Chemistry, 1997
Although international standards concerning the performance of analytical laboratories, such as IS0 25 or EN 45001, indicate that the limits of application of analytical methodologies must be established, the calculation of detection limits in multivariate analysis is made more difficult in practice for two reasons: on the one hand, the theoretical problem of obtaining the appropriate estimators [ 1 ] and on the other, the lack of suitable calculation programs. This article discusses a new algorithm for calculating detection limit estimators in multicomponent analysis, where the direct calibration models are used. The methodology developed is based on the statistical theory of hypothesis tests applied to the concentration domain [ 21 and takes into account the p probability of falsely accepting the absence of analyte, something which has been often ignored in the approaches developed so far. The performance of the new estimator is assessed by comparing the results with those obtained with two previously developed approaches. 2. The algorithm and computer program The program is written in Matlab language (Mfile). Fig. 1 shows the flow diagram of the program. The inputs of the program are the calibration set's matrices of responses and concentrations (R and C, respectively), the unknown sample's vector (or *Corresponding author.
Accreditation and Quality Assurance, 1999
An approach to the assessment of the limit of detection and the limit of quantitation using uncertainty calculation is discussed. The approach is based on the known evaluation of the limits of detection and quantitation as concentrations of the analyte equal to three and ten standard deviations of the blank response, respectively. It is shown that these values can be calculated as the analyte concentrations, for which relative expanded uncertainty achieves 66% and 20% of possible results of the analyte determination, correspondingly. For example, the calculation is performed for the validation of a new method for water determination in the presence of ene-diols or thiols, developed for analysis of chemical products, drugs or other materials which are unsuitable for direct Karl Fischer titration. A good conformity between calculated values and experimental validation data is observed.
Limits of quantitation for laboratory assays
Journal of the Royal Statistical Society: Series C (Applied Statistics), 2005
A common problem with laboratory assays is that a measurement of a substance in a test sample becomes relatively imprecise as the concentration decreases. A standard solution is to establish lower limits for reliable measurement. A quantitation limit is a level above which a measurement has sufficient precision to be reliably reported. The paper proposes a new approach to defining the limit of quantitation for the case where a linear calibration curve is used to estimate actual concentrations from measured values. The approach is based on the relative precision of the estimated concentration, using the delta method to approximate the precision. A graphical display is proposed for the assessment of estimated concentrations, as well as the overall reliability of the calibration curve. Our research is motivated by a clinical inhalation experiment. Comparisons are made between the approach proposed and two standard methods, using both real and simulated data.