Inter-laboratory variation

Zenger, V.E. et al., Quantitative flow cytometry Inter-laboratory variation, Cytometry, 33, 138, 1998. 

The 95% confidence interval amounted to 1.3 log units, which corresponds to a scatter in the ATdoc values by a factor of 20. Burkhard (2000) argues that the uncertainty in Eq. 3.25 originates partly from inter-laboratory variation, and partly from differences in DOC quality. In view of the wide range of DOC sources included in Eq. 3.25, it does not seem likely that the uncertainties in any ATdoc encountered would be more than 1.3 log units. Hence, the worst-case estimate (maximum sorption of dissolved phase residues by DOC) can be described by... 

In analytical chemistry, validation of the analytical methods is of utmost importance [4,5]. One of the aspects of this validation is the robustness of analytical methods against variations in experimental circumstances. The term experimental circumstances is very broad it might even include inter-laboratory variation. In this book, only intra-laboratory experimental conditions are considered. No explicit attention is given to inter-laboratory variations, although some of the presented methodology might be useful in that area. 

Two round robin testing programs were carried out using spheres, tablets and extrudates. Testing conditions were controlled in order to minimize inter-laboratory variations however, the use of... 

A test method for single pellet crush testing of catalytic spheres and tablets was developed by ASTM Committee D-32 on Catalysts. A procedure for the single pellet crush strength of extrudates that gives satisfactory interlaboratory variation is yet to be attained. An alternate method will test the assumption that the inter laboratory variations, seen in all round robins, were caused by moisture absorption during testing and the use of a specialized anvil in the test instrument. 

Precision refers to the degree of repeatability under the stated conditions of the method. It is expressed as percent relative standard deviation (% RSD) for a statistically significant number of analyses of samples. Precision provides a measure of day to day, analyst to analyst and instrument to instrument variation on a routine basis. The precision data provided in support are standard deviation, % RSD, confidence intervals and may also include inter laboratory variations. 

Further studies should be undertaken to standardize the hydrolytic and oxidation procedures and improve accuracy of the procedures to further reduce inter-laboratory variation. 

Evaluate the overall inter-laboratory variation, and its random and systematic components. 

The third and fourth rows of the table can be used to show that D = 0.244 and T = 49.33. Equations (4.15) and (4.16) then show that the overall variance and the measurement variances are (5.296) and (1.383) respectively. These can be compared as usual using the f-test, giving F = 14.67. The critical value, 8,8/ is 3.44 P= 0.05), so the inter-laboratory variation cannot simply be accoimted... 

These are only intended to indicate which substances should be investigated further via in-vivo studies. Thus the relevance of these in-vitro tests to real life is not known and in addition they suffer from considerable inter-laboratory variation. 

Consequently, it was proposed to define (Burns et al. [2005]) Robustness of an analytical procedure is the property that indicates insensitivity against changes of known operational parameters on the results of the method and hence its suitability for its defined purpose and Ruggedness of an analytical procedure is the property that indicates insensitivity against changes of known operational variables and in addition any variations (not discovered in intra-laboratory experiments) which may be revealed by inter-laboratory studies (Burns et al. [2005]). 

Property of an analytical procedure that indicates insensitivity against changes of known operational variables and in addition any variations (not discovered in intra-laboratory experiments) which may be revealed by inter-laboratory studies. 

Lee and Chau [66] have discussed the development and certification of a sediment reference material for total polychlorobiphenyls. Alford Stevens et al. [49] in an inter-laboratory study on the determination of polychlorobiphenyls in environmentally contaminated sediments showed the mean relative standard deviation of measured polychlorobiphenyl concentrations was 34%, despite efforts to eliminate procedural variations. Eganhouse and Gosset [67] have discussed the sources and magnitude of bias associated with the determination of polychlorobiphenyls in environmental sediments. Heilman [30] studied the adsorption and desorption of polychlorobiphenyl on sediments. 

A further advancement comes from inter-laboratory comparison of two standards having different isotopic composition that can be used for a normalization procedure correcting for all proportional errors due to mass spechomehy and to sample preparation. Ideally, the two standard samples should have isotope raUos as different as possible, but still within the range of natural variations. There are, however, some problems connected with data normalization, which are still under debate. For example, the CO2 equilibration of waters and the acid extraction of CO2 from carbonates are indirect analytical procedures, involving temperature-dependent fractionation factors (whose values are not beyond experimental uncertainties) with respect to the original samples and which might be re-evaluated on the normalized scale. 

In a protocol about collaborative studies [10] it is also considered what is called preliminary estimates of precision. Among these the protocol defines the total within-laboratory standard deviation . This includes both the within-run or intra-assay variation (= repeatability) and the between-run or inter-assay variation. The latter means that one has measured on different days and preferably has used different calibration curves. It can be considered as a within-laboratory reproducibility. These estimates can be determined prior to an interlaboratory method performance study. The total within-laboratory standard deviation may be estimated fi-om ruggedness trials [10]. 

Intra-laboratory CVs range from 9.9% for ethylmalonate (at 102 pmol/1) to 40.7% for suberylglycine (at 48.6 pmol/1) and inter-laboratory CVs from 42.5% for ethylmalonate (at 102 pmol/1) to 757.4% for tiglyglycine at 83.5 pmol/1. This wide variation is also accompanied by marked variability in the reference ranges used by different laboratories an example is shown (Fig. 1.2.1) for a single return from 18 respondents who quantitated ethylmalonate in a single sample (sample 109) and reported both the result and the upper limit of normal used by their laboratory. Clearly the clinical significance of this apparently extreme variability depends upon the clinical context... 

G Sarwar, DA Christensen, AJ Finlayson, M Friedman, LR Hackler, SL Mackenzie, PL Pellett, R Tkachuk. Inter- and intra-laboratory variation in amino acid analysis of food proteins. J Food Science 48 526-531, 1983. 

Heavy oils and residua can be separated into a variety of fractions using a myriad of different techniques that have been used since the beginning of petroleum science (Speight, 1999). However, the evolution of these techniques has been accompanied by subtle inter-laboratory (and even intra-laboratory) variations to an extent that many of the nuclear fractionation procedures appear to bear very little relationship to one another. 

A common example where ANOVA can be applied is in interlaboratory trials or method comparison. For example, one may wish to compare the results from four laboratories, or perhaps to evaluate three different methods performed in the same laboratory. With inter-laboratory data, there is clearly variation between the laboratories (between sample/treatment means) and within the laboratory samples (treatment means). ANOVA is used in practice to separate the between-laboratories variation (the treatment variation) from the random within-sample variation. Using ANOVA in this way is known as one-way (or one factor) ANOVA. 

The largest commercially available datasets are the Physical Properties (PHYSPROP) and AQUASOL databases ca. 6000 compounds in each database). The AQUASOL database has been published as a book. Furthermore, two relatively large sets of aqueous solubility data models were used in many other studies.Data from the AQUASOL database had an interlaboratory variation of about a = 0.49 log-units (as estimated for A=1031 molecules).Moreover, large inter-laboratory errors mask the influence of temperature, and differences as large as AT = 30 °C do not increase this error. In-house models developed at pharmaceutical companies could be based on similar or even larger numbers of measurements. For example, about 5000 molecules were used to develop a model at Bayer Healthcare AG. " ... 

Intercomparison exercises. Participation in intercomparison exercises is a unique opportunity for a laboratory to assess the quality of its analytical capability. Also, they are very useful for estimating the inter-laboratory coefficient of variation for that specific analysis. 

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