Biomedical subjects

W Horwitz

Publications and source records attributed to W Horwitz.

39 records · Page 3Linked to original sources

PubMedDate not supplied

Variability associated with analytical methods used to measure aflatoxin in agricultural commodities.

A total of 1019 analytical precision estimates obtained from method-performance (collaborative) studies for mycotoxins published through 1991 were sorted by type of variance measurement, type of analytical method, and type of agricultural commodity. Precision estimates for total aflatoxin were sorted into 2 precision measurements (among-laboratories and within-laboratory), 3 analytical methods (thin-layer chromatography [TLC], liquid chromatography [LC], and enzyme-linked immunosorbent assay [ELISA]), and 11 agricultural commodities. Sufficient data existed to study the analytical variability (precision) associated with 36 sorted combinations (of a possible 66). In all but one combination (within-laboratory, barley, and TLC), the variance (V) was a function of total aflatoxin concentration (C). A power function of the form V = aCb, where a and b are constants, describes the relationship between variance and aflatoxin concentration. The coefficients a and b were determined from regression analysis. When results were pooled across all agricultural commodities, LC had the lowest analytical variability while ELISA had the highest. For a given method, among-laboratories variability was approximately double the within-laboratory variability. These analytical variability estimates can be coupled with previously determined variability estimates of sampling and sample preparation to determine the performance associated with specific test procedures used to inspect agricultural commodities for aflatoxin.

Aflatoxins↗

PubMedDate not supplied

Uncertainty--a chemist's view.

Complete characterization of the performance of analytical methods requires an evaluation of the halo of uncertainty bracketing the reported result. Achieving a satisfactory estimate of this uncertainty is more important than how this estimate is produced. Enumeration of all conceivable error components--the so-called error budget approach--is one way to estimate the uncertainty, but it is not the only way. In fact, when applied to analytical chemistry this approach is likely to (1) overlook important variables and double count others, (2) avoid considering unknown and unknowable interactions and interferences, and (3) adjust for missing variables with an uncontrollable "Type B" component. The problem is one of experimental design. Alternative and more efficient ways of estimating uncertainty in analytical chemistry include the Youden ruggedness procedure, accompanied by a bonus of optimization, and the all-encompassing interlaboratory method-performance trial.

Chemistry Techniques, Analytical↗

PubMedDate not supplied

A simple method for evaluating data from an interlaboratory study.

Large-scale laboratory- and method-performance studies involving more than about 30 laboratories may be evaluated by calculating the HORRAT ratio for each test sample (HORRAT = [experimentally found among-laboratories relative standard deviation] divided by [relative standard deviation calculated from the Horwitz formula]). The chemical analytical method is deemed acceptable per se if HORRAT approximately 1.0 (+/- 0.5). If HORRAT is > or approximately 2.0, the most extreme values are removed successively until an "acceptable" ratio is obtained. The laboratories responsible for the extreme values that are removed should examine their technique and procedures. If > or approximately 15% of the values have to be removed, the instructions and the methods should be examined. This suggested computation procedure is simple and does not require statistical outlier tables. Proposed action limits may be adjusted according to experience. Data supporting U.S. Environmental Protection Agency method 245.1 for mercury in waters (manual cold-vapor atomic absorption spectrometry), supplemented by subsequent laboratory-performance data, were reexamined in this manner. Method-performance parameters (means and among-laboratories relative standard deviations) were comparable with results from the original statistical analysis that used a robust biweight procedure for outlier removal. The precision of the current controlled performance is better by a factor of 4 than that of estimates resulting from the original method-performance study, at the expense of rejecting more experimental values as outliers.

Chemistry Techniques, Analytical↗