In some metrology applications multiple results of measurement for a common measurand are obtained and it is necessary to determine whether the results agree with each other. A result of measurement based on the Guide to the Expression of Uncertainty in Measurement (GUM) consists of a measured value together with its associated standard uncertainty. In the GUM, the measured value is regarded as the expected value and the standard uncertainty is regarded as the standard deviation, both known values, of a state-of-knowledge probability distribution. A state-of-knowledge distribution represented by a result need not be completely known. Then how can one assess the differences between the results based on the GUM? Metrologists have for many years used the Birge chisquare test as 'a rule of thumb' to assess the differences between two or more measured values for the same measurand by pretending that the standard uncertainties were the standard deviations of the presumed sampling probability distributions from random variation of the measured values. We point out that this is misuse of the standard uncertainties; the Birge test and the concept of statistical consistency motivated by it do not apply to the results of measurement based on the GUM. In 2008, the International Vocabulary of Metrology, third edition (VIM3) introduced the concept of metrological compatibility. We propose that the concept of metrological compatibility be used to assess the differences between results based on the GUM for the same measurand. A test of the metrological compatibility of two results of measurement does not conflict with a pairwise Birge test of the statistical consistency of the corresponding measured values.