Method variability

However, other approaches may be equally valid. For instance, some inter-laboratory assessments utilise samples that have been spiked with a known concentration of an impurity(ies). Thus if the receiving laboratory meets the pre-determined acceptance criterion this constitutes an acceptable transfer. The transfer protocol is pre-approved by both transferring and receiving laboratory(ies) and stipulates all of the details of methodology, samples, acceptance criterion and appropriate method variability. 

Using cyclohexylamine, as M ef, the data for various enantiomeric mixtures ofl-(l-naphthyl)ethylamine (M) display a linear relationship between RPIj /RPP and ee. Enantiomeric impurieties as small as about 2% can currently be detected with this method." " Variable-temperature FT-ICR-MS measurements of the ligand... 

The two-factor interaction effects and the dummy factor effects in FF and PB designs, respectively, are often considered negligible in robustness testing. Since the estimates for those effects are then caused by method variability and thus by experimental error, they can be used in the statistical analysis of the effects. Requirement is that enough two-factor interaction or dummy factor effects (>3) can be estimated to allow a proper error estimate (see Section VII.B.2.(b)). 

Ionization changes can be efficiently corrected with the use of an isotopically labeled IS, which possesses identical ionization response and fragmentation pattem. Therefore, deuterated IS can be used to correct both the overall method variability (e.g., sample preparation, injection, electrophoretic process, etc.) as well as matrix effects since the amount of suppression from interferents is expected to be similar. However, the total concentration of analyte and IS should be below the saturation of the ionization process. Guidelines to obtain a reproducible CE—MS method were published by Ohnesorge et al. and took into account the use of an isotopically labeled IS. 

The balance of this paper is concerned with a presentation of the details of the gas purging and adsorbent trapping method for the analysis of very volatile compounds in water samples. A number of method variables have been studied during the last five years, and the method has been applied to a wide variety of sample types. There have been a number of publications which are cited and may be consulted for additional information (B-12). 

Table I contains a list of some of the compounds that have been submitted to this type of analysis. The recovery data is intended to be illustrative only since recoveries depend strongly on several important method variables. Recoveries are expressed as a percentage of the amount added to organic free water. The purge time was 11-15 minutes with helium or nitrogen, the purge rate was 20 ml/minute at ambient temperature, and the trap was Tenax followed by Silica Gel. Data from the 5 ml sample was obtained with a custom made purging device and either flame ionization, microcoulo-metric, or electrolytic conductivity GC detectors. Data from the 25 ml sample was obtained with a Tekmar commercial liquid sample concentrator and a mass spectrometer GC detector using CRMS.

In the hopes of accessing similar molecules that would contain C-6 functionalization, our group explored the cycloisomerization of such alkyne hemiketals as 152.70 Compound 152 was prepared by addition of ethynyltrimethylsilane to 5-0-terf-butyl-diphenylsilyl-2,3-0-isopropylidene-D-ribonolactone (151), followed by desilylation (25% over two steps). Trie thy lamine-mediated cycloisomerization71 provided an oxepinone, compound 153, in 41% yield. 1,2-Reduction of the enone functionality followed by acetylation under standard conditions provided 154 in 56% yield over two steps as a 3 1 ratio of diasteromers (the favored diastereomer is shown in Scheme 24). A small group of oxepines were prepared by this method. Variability in the yield of the cyclization step, which was moderate at best, has prevented this route from being applied more generally for the preparation of oxepines. 

The interlaboratory results obtained from the analysis of defined standard solutions, but also from the analysis of sediment extracts prepared either by the coordinator of the study or by the participants themselves, also provide a measure of the variation between laboratories. The results show that the interlaboratory reproducibility ranges from 6.5% for the defined dioxin sample to 27.9% for the sediment sample extracted by the participants themselves. As was mentioned before, the reproducibility for this last sample is relatively high and most presumably due to the introduction of extra handlings (extraction and cleanup) to the total procedure. In addition, the fact that not all the participants had prior experience with the extraction protocol to be used could have added to the increase in variability of the process. Furthermore, the dilution factor was not dictated. This also introduces a certain degree of variation. For the reproducibility of the DR CALUX bioassay itself and not caused by differences in operating extraction conditions, the maximum variation between laboratories was observed to be 18.0%. The results for the sediment extract samples can also be used to estimate the method variability for extracts, that is, based on samples of unknown composition. Again, given the intra-as well as the interlaboratory variations observed in this study, it appears justified to conclude that the standard deviation of the means provides a reasonable estimate of the method variability, based on the overall aver-... 

Several overall conclusions can be drawn based on the statistical evaluation of the data submitted by the participants of the DR CALUX intra-and interlaboratory validation study. First, differences in expertise between the laboratories are apparent based on the results for the calibration curves (both for the curves as provided by the coordinator and for the curves that were prepared by the participants) and on the differences in individual measurement variability. Second, the average results, over all participants, are very close to the true concentration, expressed in DR CALUX 2,3,7,8-TCDD TEQs for the analytical samples. Furthermore, the interlaboratory variation for the different sample types can be regarded as estimates for the method variability. The analytical method variability is estimated to be 10.5% for analytical samples and 22.0% for sediment extracts. Finally, responses appear dependent on the dilution of the final solution to be measured. This is hypothesized to be due to differences in dose-effect curves for different dioxin responsive element-active substances. For 2,3,7,8-TCDD, this effect is not observed. Overall, based on bioassay characteristics presented here and harmonized quality criteria published elsewhere (Behnisch et al., 2001a), the DR CALUX bioassay is regarded as an accurate and reliable tool for intensive monitoring of coastal sediments. 

The slope of the regression line will provide an idea of the sensitivity of the regression, and hence the method that is being validated. The intercept will provide an estimate of the variability of the method. For example, the ratios percent of the intercept with the variable data at nominal concentration are sometimes used to estimate the method variability. 

Ruggedness of an analytical method is the insensibility of the method for variations in the circumstance and the method variables during execution. It is important to note that statistically significant deviations are not always relevant. The purpose for which the measurement is made is a more important criterion for deciding on the ruggedness and the statistical method employed is merely a tool. 

The homogeneity should be established by testing a representative number of laboratory samples taken at random using either the proposed method of analysis or other appropriate tests such as UV absorption, refractive index, etc. The penalty for inhomogeneity is an increased variance in analytical results that is not due to intrinsic method variability. 

Rue, W.J., Fava, J.A. and Grothe, D.R. (1988) A review of inter- and intralaboratory effluent toxicity test method variability, in M.S. Adams, G.A. Chapman and W.G. Landis (eds.), Aquatic Toxicology and Hazard Assessment l(fh Volume, ASTM STP 971, American Society for Testing and Materials,... 

Should compare method performance with validation data to determine if method variability exceeds that obtained under ideal circumstances... 

S2 = Varaince association with the total product/process/ method variability... 

Data Collection Devices Modem data stations receive and store detector output and print out chromatograms complete with peak heights, peak areas, sample identification, and method variables. They are also used to program the liquid chromatograph, controlling most variables and providing for long periods of unattended operation. 

Optimization or experimental design software packages for modeling the chromatographic response as a function of one or more method variables. These can also play a key role in data management of the considerable information that results from rigorous method development exercises. 

Variable Method Variable Method Variable Method ... 

Integral methods Variable time In the variable-time method of measurement of the initial slope, the concentration of the indicator substance I is measured twice, and the time interval At required to bring about a preselected change in concentration A[I] is the important quantity (Figure 21-2, right). Since the change in concentration is a fixed preselected value, it can be incorporated with the constant in Equation (21-5) to give... 

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