Monitoring accuracy and precision ? Improvements by introducing robust and resistant statistics (original) (raw)
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Arhiv za higijenu rada i toksikologiju, 1998
Method validation is a key element in the establishment of reference methods and in the assessment of a laboratory's competence in producing reliable analytical data. Hence, the scope of the term "method validation" is wide, especially if one bears in mind the role of Quality Assurance/Quality Control (QA/QC). The paper puts validation in the context of the process generating chemical information, introduces basic performance parameters included in the validation processes, and evaluates current approaches to the problem. Two cases are presented in more detail: the development of European standard for chlorophenols and its validation by a full scale collaborative trial and the intralaboratory validation of a method for ethylenethiourea by using alternative analytical techniques.
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International Journal of Science and Research (IJSR), 2016
The current research focused on the importance of quality control for chemical analysis through instrument calibration conditions, on different organochlorine pesticides samples using standard mixture solutions. For this aim statistical quality control calculations were performed to optimize the validation of Gas chromatography mass spectrometry (GC-MS) and its compatibility range. The obtained quality control assessment results confirmed instrument method's performance in term of the instrument accuracy, excellent sensitivity and selectivity of the consequences.
TrAC Trends in Analytical Chemistry, 2004
Credibility of analytical data has never caught the public's eye more than today. The key principle for quality and reliability of results is comparability between laboratories and on a wider, international basis. In order to be comparable, analytical results must be reported with a statement of measurement uncertainty (MU) and they must be traceable to common primary references. This work focuses on traceability and uncertainty of results. We discuss different approaches to establishing traceability and evaluating MU. We place both concepts in the broader context of analytical method validation and quality assurance. We give up-to-date information in the framework of new, more exacting European and international standards, such as those from Eurachem/CITAC, IUPAC and ISO.
International Journal of Chemistry, 2011
Measurement error modeling is crucial to any assay method. Realistic error models prioritize efforts to reduce key error components and provide a way to estimate total ("random" and "systematic") measurement error variances. This paper uses multi-laboratory data to estimate random error and systematic error variances for seven analytical chemistry destructive assay methods for five analytes (Gallium, Iron, Silicon, Plutonium, and Uranium). Because these variance estimates are based on multiple-component error models, strategies are described for choosing and then fitting error models that allow for lab-to-lab variation.
Measurement uncertainty in analytical methods in which trueness is assessed from recovery assays
Analytica Chimica Acta, 2001
We propose a new procedure for estimating the uncertainty in quantitative routine analysis. This procedure uses the information generated when the trueness of the analytical method is assessed from recovery assays. In this paper, we assess trueness by estimating proportional bias (in terms of recovery) and constant bias separately. The advantage of the procedure is that little extra work needs to be done to estimate the measurement uncertainty associated to routine samples. This uncertainty is considered to be correct whenever the samples used in the recovery assays are representative of the future routine samples (in terms of matrix and analyte concentration). Moreover, these samples should be analysed by varying all the factors that can affect the analytical method. If they are analysed in this fashion, the precision estimates generated in the recovery assays take into account the variability of the routine samples and also all the sources of variability of the analytical method. Other terms related to the sample heterogeneity, sample pretreatments or factors not representatively varied in the recovery assays should only be subsequently included when necessary. The ideas presented are applied to calculate the uncertainty of results obtained when analysing sulphides in wine by HS-SPME-GC.
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Analytica Chimica Acta, 1995
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Evaluation of the analytical method performance for incurred samples
Analytica Chimica Acta, 2003
A methodology for the evaluation of the performance of an analytical method for incurred samples is presented. Since this methodology is based on intra-laboratory information, it is suitable for analytical fields that lack reference materials with incurred analytes and it can be used to evaluate the analytical steps prior to the analytical portion, which are usually excluded in proficiency tests or at the certification of reference materials. This methodology can be based on tests performed on routine samples allowing the collection of information on the more relevant combinations analyte/matrix; therefore, this approach is particularly useful for analytical fields that involve a high number of analyte/matrix combinations, which are difficult to cover even considering the frequent participation in expensive proficiency tests.
Journal of AOAC INTERNATIONAL, 1997
A statistical methodology to verify the trueness of an analytical method in the presence of corrigible systematic errors is presented. This protocol enables detection of constant and proportional components of error. By using the data set obtained in the Youden calibration with different sample test portions, the constant component of the error (Youden blank) can be determined. An analysis of covariance was applied to 3 calibration curves established with standard solutions and with standard additions to 2 different sample test portions. The slopes were compared, and the presence of any matrix-analyte interaction was detected. A method for removing the numerical components of systematic errors is proposed: a calculation procedure to obtain a correct analytical result and a statistical test to verify the correctness of analyte contents obtained from different calibrations. For demonstration purposes, the protocol was applied to spectrofluorometric determination of oxalates in spinach...
Journal of the Association for Laboratory Automation, 2003
A high-throughput analytical characterization system was developed for quality control support of a central sample collection resource. This system utilizes liquid chromatography mass spectrometry with in-house developed data automation applications. Continuous operation of analytical instrumentation is accomplished by fully automating sample submission and report processing functions. Comprehensive analytical information characteristic of quality, chemical, and physical properties (e.g. relative purity, detection sensitivity, LogD) are automatically transferred to an on-line database. The application of this database for detailed quality assessment of a small sample library (ca. 24,000 compounds) is demonstrated.