Minimising systematic errors

A.2.5 Minimising systematic errors 3B. Statistical Validation 3B.1 Introduction 3B.2 Statistical validation... 

The enthalpy of reaetion for the formation of ThF ", n = 1-3, have been determined ealorimetrieally at 25°C in a 0.5 M NaC104 ionie medium. The experiments were made by titrating a test solution of 20 mM Th" with an initial pH (presumably -logic PT ]) of 1.1 with a solution of 0.1000 M NaF. In addition the authors made a separate experiment to determine the enthalpy of protonation of P and the enthalpy of dilution of the NaF titrant. The experiments were earned out until precipitation occurred at 1.7. The equilibrium constants used to interpret the titration data were taken from [1982MAR/SM1]. The authors have use state of the art equipment and methodology and taken care to minimise systematic errors. This is very important in view of the small reaction enthalpies, corresponding to about 40 ml for the individual additions of the titrant. This is a very precise experimental study and the conclusions drawn by the authors are accepted by this review. 

Phenolic antioxidant O 10 was varied between 0 % and 0.044 %. Moreover, each stabiliser combination was prepared twice, independently, to minimise systematic errors. 

The outcome of the different exercises should be discussed among all participants in technical meetings, in particular to identify random and/or systematic errors in the procedures. Whereas random errors can be detected and minimised by intralaboratory measures, systematic errors can only be identified and eliminated by comparing results with other laboratories/techniques. When all steps have been successfully evaluated, i.e. all possible sources of systematic errors have been removed and the random errors have been minimised, the methods can be considered as valid. This does not imply that the technique(s) can directly be used routinely and further work is likely to be needed to test the robustness and ruggedness of the method before being used by technicians for daily routine measurements . 

Analytical measurements should be made with properly tested and documented procedures. These procedures should utilise controls and calibration steps to minimise random and systematic errors. There are basically two types of controls (a) those used to determine whether or not an analytical procedure is in statistical control, and (b) those used to determine whether or not an analyte of interest is present in a studied population but not in a similar control population. The purpose of calibration is to minimise bias in the measurement process. Calibration or standardisation critically depends upon the quality of the chemicals in the standard solutions and the care exercised in their preparation. Another important factor is the stability of these standards once they are prepared. Calibration check standards should be freshly prepared frequently, depending on their stability (Keith, 1991). No data should be reported beyond the range of calibration of the methodology. Appropriate quality control samples and experiments must be included to verify that interferences are not present with the analytes of interest, or, if they are, that they be removed or accommodated. 

In most experimental studies, there are two sources of variation or error. The first arises from the intrinsic variability in individual measurements or observations that are all obtained in the same way. The second arises from errors in the apparatus or procedures which affect all of the measurements in a similar way. This type of variation, which leads to a consistent deviation from the correct or true measurement is termed systematic error. It is important that these two sources of error are clearly distinguished. The first (intrinsic variability) can be analysed statistically, and replicated measurements will give an estimate of the precision of the measurement or procedure. These errors are termed statistical errors. This does not mean, however, that the result obtained is necessarily an accurate or true one. Pipettes may have become uncalibrated, or solutions have deteriorated there are many ways in which systematic errors can lead to false values, and attention to calibration and independent verification of apparatus or procedures is essential to minimise the risk of this happening. Systematic errors are potentially much more problematic in biochemical work, since these can easily occur without the experimenter being aware of them. 

By helping to ensure that all personnel will use exactly the same procedures for the operations described therein, the SOPs may be looked at as an instrument to minimise the introduction of random error, due to individually varied procedures, into a study. On the other hand, the SOPs need to be written by persons who are experienced in the procedures to be described, and thus the introduction of systematic error into studies should also become minimised. 

Sample dilution is often required to match the expected analyte concentration with the dynamic concentration range of the analytical procedure. Clinical analyses, where several parameters are routinely determined in large sample batches, is a good example of this requirement. Extensive dilution of biological fluids is common practice in view of the high analyte concentration and the need to minimise matrix effects. However, sample dilution is usually time-consuming, can degrade precision and lead to systematic errors. 

The realisation that every laboratory determination that is carried out is associated with both random and systematic errors has had a major impact on laboratory medicine in the last thirty years. It is also at the heart of quality control and quality assurance procedures which are primarily concerned with understanding the sources of such errors and their suppression or minimisation (Whitehead, 1977 Aitio, 1981 Taylor, 1987). However, it has been pointed out by Broughton (1983) that all laboratories may carry out some form of "quality control" but this is often designed to give retrospective reassurance rather than provide prospective action. The dual concepts of bias and precision in laboratory medicine are well known, but not always appreciated even by users of reference materials (Taylor. 1985 Taylor, 1987). By definition an unbiased result should be the "true" result, but in practice this is hardly ever achieved. The nearest approach to a true value is generally obtained by using a certified reference material and a definitive method, but these ideals are unobtainable in the case of most trace metal analyses. 

If referring to usual applications, then the most questionable of all the simplifications listed above is the assumption that the activities are equal to the molar concentrations. Nevertheless, it should be pointed out that only the ratios appear in the final equation, which ends up minimising the impact of such systematic errors. 

A systematical approach of sample preparation methods and optimisation of the quality aspects of sample preparation may enhance the efficiency of total analytical methods. This approach may also enhance the quality and knowledge of the methods developed, which actually enhances the quality of individual sample analyses. Unfortunately, in bioanalysis, systematical optimisation of sample preparation procedures is not common practice. Attention to systematical optimisation of assay methods has always been mainly on instrumental analyses problems, such as minimising detection limits and maximising resolution in HPLC. Optimisation of sample extraction has often been performed intuitively by trial and error. Only a few publications deal with systematical optimisation of liquid-liquid extraction of drugs from biological fluids [3,4,5]. 

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