Deviation of a single observation from the hypothetical true value. Guidelines for computing the magnitude of...

In clinical work as well as in intervention studies, decisions concerning further follow-up or treatment of individuals are often based on a single measurement of each variable considered. If the measured variable for a certain individual varies considerably with time due to biological intra-individual variation and methodological variation, we would intuitively be sceptical to such decisions. The intra-individual variations, i.e. a composition of both biological and methodological variations, could be regarded as noise in the measurements. A more precise definition of noise would be: 'Noise is defined as random variations from a person's true value (hypothetical) in a time interval for which the true value is assumed constant.' Methodological variation, in particular, will sometimes lead to misclassifications (with respect to a given cut-off point) of a single measurement versus a person's true value. In this paper we will present formulas and tables which will help the reader to quantify such misclassifications in his/her own material.